Method for optimizing supplier selection and quantity allocation based on evolutionary optimization

Abstract

A method for optimizing supplier selection and quantity allocation based on evolutionary optimization is disclosed. The present invention provides a method for optimizing supplier selection and quantity allocation which, when manufacturing or assembly enterprises source parts, optimizes the efficiency of time and cost in supplier selection, thereby mitigating risks related to supplier selection, and improving the reliability and adaptability of the selection as well as profitability.

Description

Optimization method for supplier selection and volume allocation based on evolutionary optimization

[0001] The present invention relates to a method for optimizing supplier selection and volume allocation based on evolutionary optimization.

[0002] For manufacturing and assembly companies, the task of selecting the optimal supplier for parts and allocating volume to each supplier is critical. Given the existence of a wide range of potential candidate suppliers and the varying conditions regarding product quality, cost, and lead times among them, it is necessary to optimize the time and cost efficiency of supplier selection.

[0003] Existing supplier selection and volume allocation methods have a problem in that they are inefficient to apply to the actual production situations of manufacturing and assembly companies because they focus on solving individual single goals rather than integrating the various objectives involved in supplier selection, such as product quality, cost, and delivery time.

[0004] Optimization methods based on genetic algorithms have been effectively utilized to solve complex problems, such as selecting the optimal supplier from a wide range of potential candidate suppliers; however, there is still room for improvement to address actual individual tasks and enhance their effectiveness and applicability.

[0005] In addition, generally, as shown in Fig. 9, a ship is built in the order of basic design, shipbuilding design, production design, and ship assembly after a shipbuilding company receives an order from a shipbuilding orderer, and is finally delivered to the shipbuilding orderer. Here, Basic Design is the stage of determining the basic performance and main dimensions of the ship; Ship Design is the stage of completing detailed design drawings for final approval by the classification society and the shipowner based on the contents of the basic design; Production Design is the stage of creating work drawings and instructions that can be immediately used for actual manufacturing and assembly; and Hull Assembly & Outfitting is the stage of actually manufacturing and assembling the ship according to the production design.

[0006] Meanwhile, since the construction of a ship requires a variety of materials, the accurate delivery of necessary materials is a prerequisite. In particular, to ensure compliance with the contractual delivery deadline, materials of the required quality and specifications must be supplied in a timely manner according to the construction schedule. To this end, various methods for delivering ship materials are being proposed.

[0007] However, since material orders are generally placed after work drawings are drawn up based on production designs, if issues arise with material delivery due to circumstances at the supplier after the order is placed, the shipbuilding period is extended, which ultimately leads to delays in the ship's delivery schedule. Yet, conventional methods for supplying ship materials merely ensure timely delivery by considering the shipbuilding schedule or material supply information, or simply rely on material delivery contracts and management based on material types or information stored in existing databases.

[0008] Therefore, it is necessary to develop optimization methods for supplier selection and volume allocation based on evolutionary optimization.

[0009] The objective of the present invention is to solve the problems of the prior art as described above by providing a method for optimizing supplier selection and volume allocation based on evolutionary optimization.

[0010] Another objective of the present invention is to provide a method for optimizing supplier selection and volume allocation with improved accuracy, reliability, profitability, and productivity based on an improved genetic algorithm by applying regional improvement and row-based crossover.

[0011] Another objective of the present invention is to save the time and cost required for the supplier selection and volume allocation process by using a method for optimizing supplier selection and volume allocation.

[0012] Another objective of the present invention is to provide a ship material delivery system and a delivery method configured to enable the delivery of pre-production materials at a pre-production design stage for faster ship construction.

[0013] According to one aspect of the present invention, an optimization method for supplier selection and quantity allocation is provided, comprising: (a) generating an initial chromosome population including an initial chromosome having an initial gene composed of a supplier and an allocation of said supplier; (b) evaluating each chromosome of said initial chromosome population using an objective function; (c) selecting said evaluated chromosome as a parent chromosome according to fitness; (d) generating offspring chromosomes by applying mutations to said selected parent chromosomes; (e) updating said parent chromosomes by replacing said parent chromosomes of step (c) with said offspring chromosomes; (f) checking whether said updated parent chromosomes satisfy fitness, and if not satisfied, repeating steps (b), (c), (d), and (e) until fitness is satisfied; and (g) outputting a final chromosome including a final supplier and an allocation that satisfies fitness.

[0014] Additionally, the initial chromosome of step (a) may be represented as a two-dimensional matrix including a supplier and the supplier's allocation amount.

[0015] In addition, the objective function of step (b) may be represented by Equation 1.

[0016] [Equation 1]

[0017]

[0018] In the above Equation 1,

[0019] And,

[0020] The above α is a weighting factor assigned to the price of the component provided by the supplier, and

[0021] The above β is a weighting factor assigned to the manufacturing time of the component provided by the supplier, and

[0022] The above γ is a weighting factor assigned to the demand for components provided by the supplier, and

[0023] And,

[0024] And,

[0025] And,

[0026] is the ratio of each component allocated to the selected supplier, and

[0027] N is the total number of suppliers (i: supplier index), and

[0028] M is the total number of components (j: component index), and

[0029] P ij is the price of the j-th component provided by the i-th supplier, and

[0030] T ij is the manufacturing time of the j-th component at the i-th supplier, and

[0031] D j is the demand for the j-th component, and

[0032] B j is the budget of the j-th component, and

[0033] Cap ij is the capacity of the i-th vendor for the j-th component, and

[0034] PC ij is the process capability (%) of the i-th vendor for the j-th component.

[0035] In addition, the evaluation using the objective function in step (b) may be performed using one or more selected from the group consisting of Z-transform and linear scaling.

[0036] In addition, the above Z-transform may be performed using the following Equation 2.

[0037] [Equation 2]

[0038]

[0039] In the above Equation 2,

[0040] is a representation value of a 2-D matrix chromosome, preferably a representation value of a 2-D matrix chromosome that numerically represents a potential solution for selected suppliers and components, and

[0041] is the mean value of the representative values ​​of the 2-D matrix chromosomes, and

[0042] is the standard deviation value of the representative value of the 2-D matrix chromosome.

[0043] In addition, the above linear scaling may be performed using the following Equation 3.

[0044] [Equation 3]

[0045]

[0046] In the above Equation 3,

[0047] Is Representative values ​​of a 2-D matrix chromosome, preferably representative values ​​of a 2-D matrix chromosome that numerically represent potential solutions for selected suppliers and components, and

[0048] Is It is the minimum value of the representative value of the 2-D matrix chromosome, and

[0049] is the maximum value of the representative value of the 2-D matrix chromosome, and

[0050] a and b are scale constants, respectively, and

[0051] 0 ≤ a ≤ 1 and,

[0052] 0 ≤ b ≤ 1.

[0053] The above a and b each have the above ranges to ensure that superior individual chromosomes are preferred but not excessively preferred.

[0054] Additionally, in step (c), a fitness proportionate selection mechanism may be used to assign fitness values ​​to each chromosome and select parent chromosomes according to the magnitude of the fitness values.

[0055] Additionally, step (d) may include (d-1) a step of introducing row-based crossover to the selected parent chromosomes; (d-2) a step of introducing random mutations to the parent chromosomes into which row-based crossover has been introduced; and (d-3) a step of performing local improvement on the parent chromosomes into which random mutations have been introduced to generate offspring chromosomes.

[0056] In addition, the row-based crossover of step (d-1) can be performed with a crossover rate of 60 to 80 percent, and by performing it with said crossover rate, the relationships between rows can be preserved and structural integrity maintained.

[0057] In addition, random mutations in step (d-2) can be introduced at a mutation rate of 0.06 to 0.14%, and by introducing the mutation rate, sufficiently small mutations can be maintained so that the algorithm can evolve through each generation.

[0058] In addition, the local improvement of step (d-3) is performed by a 2-swap mechanism that crosses two valid elements to generate a new solution, and the 2-swap can be repeated until the best fit is obtained.

[0059] In addition, the above 2-swap mechanism may be performed by controlling the number of swaps of parental chromosomes and the row selection probability.

[0060] Additionally, in step (e), the fitness calculation of the parent chromosome population may be performed through a selection method.

[0061] In addition, when the fitness calculation of the above parent chromosome group is based on two or more criteria selected from a group consisting of cost, lead time, efficiency, productivity, adaptability, and robustness, it can be performed by adjusting the weight assigned to each criterion.

[0062] In addition, the above selection method may include one type selected from the group consisting of the elite selection method, the roulette wheel selection method, the rank selection method, the normal state selection method, and the tournament selection method.

[0063] In addition, the above selection method may include an elite selection method.

[0064] According to another aspect of the present invention, a computer-readable medium is provided that stores a software program for a computer to perform a method for optimizing supplier selection and quantity allocation, comprising: (a) generating an initial chromosome population including an initial chromosome having an initial gene composed of a supplier and an allocation quantity of said supplier; (b) evaluating each chromosome of said initial chromosome population using an objective function; (c) selecting said evaluated chromosome as a parent chromosome according to fitness; (d) generating offspring chromosomes by applying a mutation to said selected parent chromosome; (e) updating said parent chromosomes by replacing said parent chromosomes with said offspring chromosomes; (f) checking whether said updated parent chromosomes satisfy fitness, and if not satisfied, repeating said steps (b), (c), (d), and (e) until fitness is satisfied; and (g) outputting a final chromosome including a final supplier and an allocation quantity that satisfies said fitness.

[0065] According to another aspect of the present invention, a communication unit receiving data of an initial chromosome population comprising an initial chromosome having an initial gene composed of a supplier and an allocation of said supplier; a processor performing a method for optimizing supplier selection and allocation of quantity; and a storage unit providing storage space necessary for the processor to perform the method for optimizing supplier selection and allocation of quantity; wherein the processor comprises: (a) generating an initial chromosome population comprising an initial chromosome having an initial gene composed of a supplier and an allocation of said supplier; (b) evaluating each chromosome of said initial chromosome population using an objective function; (c) selecting said evaluated chromosome as a parent chromosome according to fitness; (d) generating offspring chromosomes by applying mutations to said selected parent chromosomes; and (e) updating said parent chromosomes by replacing said parent chromosomes with said offspring chromosomes. (f) checking whether the fitness of the updated parent chromosomes is satisfied, and if not satisfied, repeating steps (b), (c), (d) and (e) until the fitness is satisfied; and (g) outputting a final chromosome including the final supplier and the allocated quantity that satisfy the fitness; an optimization device for supplier selection and quantity allocation is provided.

[0066] In addition, the above optimization method is intended to be used for selecting suppliers and allocating quantities in a ship material delivery system, and the ship material delivery system comprises: a demander terminal (100) held by a ship company that builds the ordered ship; supplier terminals (200) each held by a plurality of material companies that supply materials required for the construction of the ordered ship; a database (300) in which data on previously built ships (ds) built by the ship company and data on previously supplied materials (dm) used for the construction of the previously built ships are matched and stored; and a brokerage platform (400) that mediates the delivery of materials required for the ordered ship between the demander terminal (100) and the supplier terminal (200); wherein the demander terminal (100) generates data on the ordered ship (DS) and data on the materials required for the order and transmits them to the brokerage platform (400), and the supplier terminal (200) [transmits] the brokerage platform (400). Accepting a provisional offer for the delivery of the required materials from the above demander terminal (100) through the above, and transmitting delivery deadline information (i2) including the expected delivery date of the required materials, delivery unit price information (i3) including the delivery unit price of the required materials, and delivery quantity information (i4) including the available delivery quantity of the required materials to the above intermediary platform (400); the above intermediary platform (400) selects one of the above built ship data (ds) closest to the above order ship data (DS), reads out at least one of the above delivered material information (i1) including the material type and delivery destination of the above delivered material from the above delivered material data (dm) matched thereto, reads out at least one of the above delivered material information (I1) including the material type of the above delivered material from the above delivered material data (DM), and selects one or more of the above delivered material information (i1) close to the above delivered material information (I1).The system may be a ship material delivery system that receives a provisional order for the delivery of the required material from the supplier terminal (200) held by the material company that is the supplier of the provided material corresponding to the selected provided material information (i1), reads out delivery period information (I2) including the delivery request date of the required material, material unit price information (I3) including the estimated delivery price of the required material, and material quantity information (I4) including the delivery quantity of the required material from the provided material data (DM) and transmits them to the supplier terminal (200) of the provided material company that received the provisional order, determines the priority of the quantified quality index, delivery date index, and cost index for the required material based on the provided material information (I1), delivery deadline information (I2), and material unit price information (I3) according to the material type of the required material, and selects one of the provided material companies that received the provisional order as the order target according to the priority.

[0067] In addition, the types of materials required above may include: a first material (M1) selected as the order target among the material companies that have been provisionally accepted by evaluating in the order of the quality index, delivery index, and cost index; a second material (M2) selected as the order target among the material companies that have been provisionally accepted by evaluating in the order of the quality index, cost index, and delivery index; and a third material (M3) selected as the order target among the material companies that have been provisionally accepted by evaluating in the order of the cost index, delivery index, and quality index.

[0068] Additionally, the first material (M1) may include a hull, the second material (M2) may include engine fittings, and the third material (M3) may include hull fittings and cabin fittings.

[0069] Additionally, the above brokerage platform (400) may exclude from the ordering target any material company among the material companies that have received a preliminary offer for the first and second materials (M1) (M2) that has a quality index lower than a preset standard index, and in the case of the first material (M1), exclude from the ordering target any material company among the material companies that have received a preliminary offer that has a delivery scheduled date exceeding a preset period compared to the delivery request date, and in the case of the third material (M3), exclude from the ordering target any material company among the material companies that have received a preliminary offer that has a delivery unit price exceeding a preset ratio compared to the delivery estimated price.

[0070] Additionally, the above optimization method is intended to be used for selecting suppliers and allocating quantities of the ship material delivery method by the ship material delivery system, and the ship material delivery method comprises: a delivery ship and delivery material data transmission step (S100) in which the user terminal (100) generates delivery ship data (DS) regarding the delivery ship and delivery material data (DM) regarding the required materials and transmits them to the intermediary platform (400); and a delivery material information reading step (S200) in which the intermediary platform (400) selects one of the previously constructed ship data (ds) closest to the delivery ship data (DS) and reads out at least one delivery material information (i1) including the material type and delivery location of the delivery material from the delivery material data (dm) matched thereto. A material delivery provisional offer step (S300) in which the above-mentioned intermediary platform (400) reads out delivery material information (I1) including at least the material type of the delivery material from the above-mentioned delivery material data (DM), selects one or more of the above-mentioned delivery material information (i1) that are close to the above-mentioned delivery material information (I1), and makes a provisional offer for the delivery of the required material to the above-mentioned supplier terminal (200) held by the above-mentioned material company that is the delivery destination of the above-mentioned delivery material corresponding to the selected above-mentioned delivery material information (i1); and a material delivery provisional offer acceptance step (S400) in which the above-mentioned supplier terminal (200) accepts the provisional offer. A step of transmitting required material information (S500) in which the above brokerage platform (400) reads out delivery period information (I2) including the delivery request date of the required material, material unit price information (I3) including the estimated delivery price of the required material, and material quantity information (I4) including the delivery quantity of the required material from the above delivery material data (DM), and transmits them to the supplier terminal (200) of the above material company that has pre-registered;The above supplier terminal (200) may include a delivery availability information transmission step (S600) in which it receives delivery deadline information (i2) including an expected delivery date of the required material, delivery unit price information (i3) including a delivery unit price for the required material, and delivery quantity information (i4) including a delivery quantity of the required material, and transmits them to the intermediary platform (400); a judgment ranking determination step (S700) in which the intermediary platform (400) determines the priority of a quantified quality index, delivery date index, and cost index for the required material based on the delivery material information (I1), delivery deadline information (I2), and material unit price information (I3) according to the material type of the required material; and an order target selection step (S800) in which the intermediary platform (400) selects one of the material companies that have made a provisional offer according to the priority as the order target.

[0071] Additionally, in the above-mentioned judgment ranking determination step (S700), the brokerage platform (400) may select the order target among the material companies that have pre-subscribed by evaluating the first material (M1), which includes the hull, in the order of the quality index, delivery index, and cost index; select the order target among the material companies that have pre-subscribed by evaluating the second material (M2), which includes the engine fittings, in the order of the quality index, cost index, and delivery index; and select the order target among the material companies by evaluating the third material (M3), which includes the hull fittings and cabin fittings, in the order of the cost index, delivery index, and quality index.

[0072] In addition, in the order target selection step (S800), the brokerage platform (400) may exclude from the order target any material company among the material companies that have received a preliminary offer for the first and second materials (M1) (M2) that has a quality index below a preset standard index, exclude from the order target any material company among the material companies that have received a preliminary offer for the first material (M1) that has a delivery scheduled date that exceeds a preset period compared to the delivery request date, and exclude from the order target any material company among the material companies that have received a preliminary offer for the third material (M3) that has a delivery unit price that exceeds a preset ratio compared to the delivery estimated price.

[0073] One embodiment of the present invention can provide a method for optimizing supplier selection and volume allocation based on evolutionary optimization.

[0074] In addition, one embodiment of the present invention can provide a method for optimizing supplier selection and volume allocation with improved accuracy, reliability, profitability, and productivity based on an improved genetic algorithm by applying region improvement and row-based crossover.

[0075] In addition, one embodiment of the present invention can save time and costs required for the supplier selection and volume allocation process by using a method for optimizing supplier selection and volume allocation.

[0076] In addition, in the ship material delivery system and method according to an embodiment of the present invention, after selecting ship data regarding an ordered ship and ship data regarding a previously built ship that is closest to the ordered ship, among the previously delivered material data used in the previously built ship matched to the selected ship data, ship data that is close to the material data regarding the materials used in the ordered ship is selected, and an evaluation priority of a quality index, a delivery date index, and a cost index is selected according to the type of material to be delivered, and an offer for the delivery of the material to be delivered is made to the delivery company that delivered the previously delivered material according to the selected evaluation priority. Accordingly, according to an embodiment of the present invention, a step for a preemptive material delivery contract is carried out at the stage prior to product design of the material after the ship order is received, so that the delivery schedule for the material to be delivered can be determined even before specific product design in the production design of the material is performed, and ultimately, it becomes possible to ensure compliance with the delivery date and deliver suitable materials.

[0077] These drawings are for reference to explain exemplary embodiments of the present invention, and therefore, the technical concept of the present invention should not be interpreted as being limited to the attached drawings.

[0078] FIG. 1 is a flowchart showing the sequence of the optimization method for supplier selection and volume allocation based on evolutionary optimization of the present invention.

[0079] FIG. 2a is a chromosome structure regarding supplier selection and volume allocation of the present invention, and FIG. 2b is a chromosome showing the actual ratio values ​​of volume suppliers and allocated volumes as a 2-D matrix.

[0080] FIG. 3 is a schematic diagram illustrating the solution procedure of the method for optimizing supplier selection and volume allocation based on evolutionary optimization of the present invention.

[0081] FIG. 4 is an example illustrating the cross, variation, and regional improvement of the present invention.

[0082] Figure 5 is an example to explain the parental chromosome selection mechanism.

[0083] Figure 6 is a graph comparing the computation time when using a conventional genetic algorithm without multi-start and local improvement and a genetic algorithm with local improvement of the present invention.

[0084] Figure 7 is a graph comparing the optimal fitness between a conventional genetic algorithm without applying local improvement and a genetic algorithm with applying local improvement according to the present invention.

[0085] Figure 8 is a graph comparing the change in average fitness over generations of a conventional genetic algorithm without applying local improvement and a genetic algorithm with applying local improvement according to the present invention.

[0086] Figure 9 is a conceptual diagram schematically showing the process of supplying materials for ships according to conventional technology.

[0087] FIG. 10 is a schematic diagram showing a ship material delivery system according to an embodiment of the present invention.

[0088] FIG. 11 is a flowchart showing a method for delivering materials for ships according to an embodiment of the present invention.

[0089] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings so that those skilled in the art can easily implement the present invention.

[0090] However, the following description is not intended to limit the present invention to specific embodiments, and detailed descriptions of related prior art are omitted if it is determined that such detailed descriptions could obscure the essence of the present invention.

[0091] The terms used herein are merely for describing specific embodiments and are not intended to limit the invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as "comprising" or "having" are intended to indicate the presence of the features, numbers, steps, actions, components, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, or combinations thereof.

[0092] Additionally, terms including ordinal numbers, such as "first," "second," etc., used below may be used to describe various components, but said components are not limited by said terms. These terms are used solely for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component.

[0093] Furthermore, when it is stated that a component is "formed" or "laminated" on another component, it should be understood that while it may be formed or laminated by being directly attached to the entire surface or one surface of the other component, there may also be other components present in between.

[0094] Hereinafter, the present invention will be described in detail regarding a method for optimizing supplier selection and volume allocation based on evolutionary optimization. However, this is presented as an example and is not intended to limit the present invention, and the present invention is defined only by the scope of the claims set forth below.

[0095] The optimization technique proposed in this invention can efficiently select the most suitable supplier from an extensive list of potential candidates, thereby minimizing costs and lead times while maximizing process capabilities with independence from the weighting of the computation process. Furthermore, it can determine how much to purchase from multiple suppliers within a specific type of expression that reduces the time required in the computation process.

[0096] Furthermore, the present invention can provide an enhanced genetic algorithm (GA) that optimizes the process of selecting multiple vendors for a single component by utilizing real-valued 2D matrix representations. Unlike conventional binary or pairwise variable representations commonly used in prior art, the proposed approach can more accurately allocate vendor ratios based on problem-specific criteria. A significant innovation of the algorithm of the present invention is the use of row-based crossover, which replaces standard techniques such as single-point or multi-point crossover. Using this method allows the algorithm to more effectively inherit useful genetic information in high-performance solutions. Additionally, the present invention employs an advanced data normalization strategy that combines Z-transformation and linear scaling. This normalization process can maintain population diversity, prevent premature convergence, and ensure a broader exploration of the solution space. By incorporating these enhancements, the algorithm of the present invention can effectively handle vendor selection problems, particularly weighted objectives such as cost minimization, delivery time, and process capability maximization.

[0097] The algorithm of the present invention can incorporate local improvement techniques using a swap mechanism. Additionally, the derived solution can be improved by replacing the initial solution with an improved version if it results in reduced costs, shorter delivery times, and higher accuracy.

[0098] The algorithm of the present invention uses an elitism selection method to evaluate the suitability of potential solutions, thereby ensuring that only the most suitable option is retained, and thereby guaranteeing that the selected solution is not only optimal but also matches the original set of criteria.

[0099] The present invention will be explained in more detail below with reference to examples. However, this is for illustrative purposes only and does not limit the scope of the invention.

[0100] FIG. 1 is a flowchart showing the sequence of the optimization method for supplier selection and volume allocation based on evolutionary optimization of the present invention, and FIG. 3 is a schematic diagram showing the solution procedure of the optimization method for supplier selection and volume allocation based on evolutionary optimization of the present invention.

[0101] The optimization technique proposed in this invention can efficiently select the most suitable supplier from an extensive list of potential candidates, thereby minimizing costs and lead times while maximizing process capabilities with independence from the weighting of the computation process. Furthermore, it can determine how much to purchase from multiple suppliers within a specific type of expression that reduces the time required in the computation process.

[0102] FIG. 2a is a chromosome structure regarding supplier selection and volume allocation of the present invention, and FIG. 2b is a chromosome showing the actual ratio values ​​of volume suppliers and allocated volumes as a 2-D matrix. Referring to FIG. 2a and FIG. 2b, the present invention can provide an enhanced genetic algorithm (GA) that optimizes the process of selecting multiple suppliers for a single component by utilizing a real-value 2D matrix representation.

[0103] FIG. 4 is a schematic diagram illustrating the crossover, mutation, and local improvement of the present invention. Referring to FIG. 4, the algorithm of the present invention can refine a group of candidate solutions through an iterative process of selection, crossover, mutation, and evolution to ultimately converge to an optimal or near-optimal solution.

[0104] Figure 3 shows the solution procedure of the methodology proposed in the present invention. Referring to Figure 3, the architecture of the enhanced genetic algorithm (GA) presented in the present invention is shown. Based on the principles of natural selection and genetics, this GA is particularly effective in solving complex optimization tasks that are difficult to solve with existing methods.

[0105] Initialization

[0106] Each chromosome generates an initial population of chromosomes representing potential solutions as a matrix corresponding to the proportion of resources allocated to various components or tasks. These proportions were normalized to verify compliance with specific constraints.

[0107] Evaluation

[0108] The fitness of each chromosome was evaluated using an objective function. The present invention uses a genetic algorithm designed for single-objective optimization, which can be further enhanced by integrating multiple objective functions using weighted combinations. This step can ensure a robust and unbiased fitness evaluation by normalizing the input data through a combination of Z-transform and linear scaling.

[0109] Selection

[0110] A fitness proportionate selection mechanism was used for parent selection, where individuals were selected based on their fitness values. As shown in Figure 5, it can be observed that lower values ​​indicate better fitness. Specifically, fitness values ​​were sorted in ascending order, and the index of the top individual was selected. Then, the selected index was used to extract the corresponding individual from the population, ensuring that the most superior individual was selected as the parent of the next generation. This approach can improve the overall robustness of the population by prioritizing the evolution of weak solutions.

[0111] Crossover

[0112] New offspring were generated by performing row-based crossovers on selected parent solutions. This technique helped in the accurate exploration of the solution space by preserving genetic diversity within the population.

[0113] Mutation

[0114] Random mutations are introduced into the offspring at a predefined mutation rate. This step is important for preventing premature convergence and maintaining the genetic diversity necessary to explore different regions of the solution space.

[0115] Local Improvement

[0116] The algorithm of the present invention generates a solution, identifies two elements within the solution matrix, and swaps them if the resulting configuration improves the fit. This precise and low-overhead tuning enhances utilization, enabling the algorithm to improve the solution without sacrificing diversity. The 2-swap method focuses on local tuning to explore the search space more effectively, thereby increasing convergence speed and providing excellent solutions, particularly in complex optimization problems. The goal of local enhancement in optimization is to improve solution quality by effectively utilizing the search space after extensive exploration steps, such as crossover or mutation, and by fine-tuning candidate solutions through targeted tuning.

[0117] Population Update

[0118] Locally improved offspring are incorporated into the population by replacing the least fit individuals. This allows the population to steadily evolve to a higher level of fitness over successive generations.

[0119] Iteration

[0120] The fitness of the entire population is continuously improved by repeating the entire process over a specified number of generations or until convergence criteria are met.

[0121] Effect of regional improvement of the present invention

[0122] Figure 6 shows the computational time deviations compared to the improved GA utilizing Local Improvement (LI) in the present invention, the standard GA, and the Multi-start method. The mean and standard deviation of the goodness-of-fit values ​​and execution times were calculated over generations. In the case of deriving simple solutions, the GA in the present invention showed a computational time similar to other optimization methods, but when finding solutions for more complex combinations, it demonstrated superior performance compared to LI and the Multi-start method in terms of computational efficiency.

[0123] Furthermore, the multi-start method is an optimization approach that initiates the search process from multiple random starting points, aiming to prevent local optima by independently exploring various regions of the solution space. The multi-start method involves running the proposed algorithm (GA only) multiple times, starting each run with a different initial population or random set of solutions. By considering multiple runs, this approach increases the likelihood of finding a global optimal in resource allocation. While the multi-start method relies on iterative and independent restarts, genetic algorithms leverage population-based evolution to maintain a balance between exploration and utilization to improve search efficiency.

[0124] Figure 7 is a graph showing the performance of the enhanced GA as the mean and standard deviation (std) obtained from multiple runs, comparing the best fitness results between the enhanced GA and the existing genetic algorithm. Since the ability of an algorithm to minimize problems is better when the fitness value is lower, it was confirmed that the GA with LI (Local Improvement) of the present invention (LIGA, Local Improvement Genetic Algorithm) is superior to the existing GA.

[0125] FIG. 10 is a schematic diagram showing a ship material delivery system according to an embodiment of the present invention.

[0126] Referring to FIG. 10, the ship material delivery system (1) according to the present embodiment is intended to deliver materials required for the construction of an ordered ship and includes a user terminal (100), multiple supplier terminals (200), a database (300), and an intermediary platform (400). The user terminal (100) is owned by the user of the materials, i.e., the shipbuilding company that builds the ordered ship, and the supplier terminal (200) is owned by the supplier of materials required for the construction of the ordered ship, i.e., each of the multiple material companies that supply the materials. Accordingly, the supplier terminal (200) will include multiple supplier terminals (200A)(200B)(200C)(200D). In the above database (300), data on previously built ships (ds) built by the ship company and data on previously delivered materials (dm) regarding materials used in the construction of the previously built ships are stored in a matched manner, and the above brokerage platform (400) mediates the delivery of the required materials between the demander terminal (100) and the supplier terminal (200).

[0127] More specifically, the demander terminal (100) generates order vessel data (DS) regarding the order vessel and delivery material data (DM) regarding the delivery target and transmits them to the intermediary platform (400). Then, the supplier terminal (200) accepts the delivery of the required materials that have been provisionally ordered through the intermediary platform (400) and transmits to the intermediary platform (400) delivery deadline information (i2) including the expected delivery date of the required materials, delivery unit price information (i3) including the delivery unit price for the required materials, and delivery quantity information (i4) including the available delivery quantity of the required materials.

[0128] Additionally, the demander terminal (100) makes a formal offer to the supplier terminal (200) for the delivery of the required materials through the brokerage platform (400). Then, the supplier terminal (200) accepts the provisional offer and formal offer for the delivery of the required materials from the demander terminal (100) through the brokerage platform (400), and transmits to the brokerage platform (400) delivery deadline information (i2) including the expected delivery date of the required materials, delivery unit price information (i3) including the delivery unit price of the required materials, and delivery quantity information (i4) including the available delivery quantity of the required materials.

[0129] The above-mentioned user terminal (100) and supplier terminal (200) may be implemented as a computer or wireless communication device capable of connecting to the platform server (100) via a network (500). Here, the computer may include a notebook, desktop, or laptop equipped with a web browser. Additionally, the wireless communication device may include a handheld-based wireless communication device such as a smartphone, smartpad, and tablet PC.

[0130] Next, the database (300) stores data on previously built ships (ds) built by the shipbuilding company and data on previously delivered materials (dm) regarding materials used in the construction of the previously built ships, which are matched with each other. The data on previously built ships (ds) and the data on previously delivered materials (dm) are compared with the data on ordered ships (DS) and delivered materials (DM) to select the material company to supply the required materials.

[0131] In this embodiment, the order vessel data (DS) and the built vessel data (ds) may include: ① basic specifications of the vessel as a primary criterion for comparing hull size; ② propulsion and engine specifications as a criterion for judging propulsion system similarity; ③ performance data as a criterion for judging performance similarity; ④ classification society and regulation information as a criterion for judging regulation application identity; ⑤ major equipment and system configurations as a criterion for judging system configuration similarity; ⑥ an overview of material configurations as a criterion for judging material level similarity; and ⑦ design criteria and construction information as a criterion for selecting the latest built vessel data. That is, the order vessel data (DS) and the built vessel data (ds) include information for selecting the built vessel that can be compared with the order vessel in terms of materials. The order vessel data (DS) and the built vessel data (ds) can be exemplified as shown in [Table 1] below.

[0132] Classification | Detailed Items Data on Ship Order (DS) | Data on Ship Built (ds) Basic Ship Specifications Ship type, Length (LOA), Width (B), Depth (D), Draft (T), Gross Tonnage (GT), Deadweight Tonnage (DWT) Values ​​defined in the order design standards Design or measured values ​​of the actual vessel under construction Propulsion and Engine Specifications Main Engine Output (MCR), Auxiliary Engine Configuration, Propulsion Type, Fuel Type Target values ​​in the basic design or specifications Actual specifications installed at the time of construction Performance Data Target speed, Range, Fuel Consumption Rate, Stability Results of basic design calculations Results of sea trials or design performance Classification Society and Regulation Information Applicable Classification Society (Class), Applicable IMO / SOLAS Regulations, Ship Registration Classification Planned information based on the order specifications History of actually approved classification societies and regulations Major Equipment and System Configuration Engine manufacturer, propulsion system, electrical / piping system, planned list of major outfitting components List of actually installed equipment Overview of Material Composition Steel type, pipe / valve material, wire type, insulation / outfitting materials Overview Basic Material Specifications Specification of Materials Used Design Basis and Construction Information Design Shipyard, Design Year, Applied Design Basis, Scheduled Construction Order Project Planning Basis Actual Shipyard, Construction Year, Process Period

[0133] In this embodiment, the delivered material data (DM) and delivered material data (dm) are intended for mutual comparison regarding the material company and may include various items capable of comparing quality index, delivery index, and cost index, as described below. First, the delivered material data (DM) and delivered material data (dm) may include: ① a material name for basic matching; ② a material code as a basic item for system identification and data matching; and ③ a material usage location / required system for material classification and search filters. Additionally, regarding the quality index, the delivered material data (DM) and delivered material data (dm) may include: ④ material specifications for evaluating basic quality based on whether the specifications match; ⑤ the supplier as an element for evaluating the supplier's quality reliability; ⑥ quality requirements / quality records as key quality evaluation items; and ⑦ management history as an evaluation element for recency and conformity. In addition, regarding the above delivery date index, the above delivery material data (DM) and delivered material data (dm) may include ⑧ the required quantity for evaluating delivery reliability, ⑨ the required delivery date for evaluating delivery compliance, ⑩ delivery conditions for evaluating logistics variables affecting delivery delays, and ⑪ expected delivery risk / delivery problem history for reflecting past delivery stability in the evaluation. Furthermore, regarding the above cost index, the above delivery material data (DM) and delivered material data (dm) may include ⑫ the delivery unit for verifying the standard unit for unit price comparison, ⑬ the estimated unit price for evaluating costs using the unit price deviation rate (actual / estimated cost), and ⑭ the material importance for reflecting the weight of costs by importance. The above delivery material data (DM) and delivered material data (dm) can be exemplified as shown in [Table 2] below.

[0134] Classification Delivered Material Data (DM) Delivered Material Data (dm) Material Type Type of material required for the ordered vessel Type of material actually delivered Material Code Shipyard or design management code number Material code for vessels already built in the DB Location / System of Use Area or system where the material will be used (hull, engine room, outfitting, etc.) Material Information Used in the Same System or Location Material Specifications Required material, dimensions, tolerances, certification conditions Material, dimensions, certification information of materials actually delivered Designated or Preferred Supplier Supplier's Past Quality History Quality Requirements / Quality Records Required Quality Grade, Inspection Standards Actual Inspection Results, Defect Rate, Approval Record Management History Design Changes, Material Certification Renewal History Quantity to be Recorded at the Time of Actual Delivery Quantity Required by Construction Process Actual Quantity Delivered Requested Delivery Date Time Required Based on Construction Schedule Actual Delivery Completion Date Delivery Conditions Delivery Method and Transport Conditions Actual Delivery Conditions and Logistics Routes Estimated Delivery Risks / Delivery Issue History Schedule Predicted Risks Actual Delay, Stockout, and Claim History Delivery Unit Quantity, Weight, Length, etc. Identical Unit System Estimated Unit Price, Budget or Standard Unit Price, Actual Delivery Unit Price, Material Importance, Importance Grade by Material Type (Shipboard Materials > Engine Materials > Outfitting Materials, etc.), Past Classification Items

[0135] Meanwhile, the above-mentioned intermediary platform (400) selects one of the above-mentioned ship data (ds) stored in the above-mentioned database (300) that is closest to the above-mentioned ship data (DS), and reads out the above-mentioned material information (i1) from the above-mentioned material data (dm) that is matched thereto. Then, the above-mentioned intermediary platform (400) reads out the delivery material information (I1) from the above-mentioned delivery material data (DM), selects one or more of the above-mentioned material information (i1) that are close to the above-mentioned delivery material information (I1), and makes a provisional offer for the delivery of the above-mentioned materials to the above-mentioned supplier terminal (200) held by the above-mentioned material company, which is the delivery destination of the above-mentioned material corresponding to the selected above-mentioned material information (i1). In other words, the above brokerage platform (400) makes a preliminary offer to at least one of the material companies that supplied the above-mentioned materials used in the construction of the above-mentioned ordering vessel and the above-mentioned recently constructed vessel, which are close to the materials required for the manufacture of the above-mentioned ordering vessel. Accordingly, the above-mentioned material information (i1) may include at least the material type and delivery location of the above-mentioned material, and the above-mentioned material information (I1) may include, for example, at least the material type of the above-mentioned material among the above-mentioned material data (DM). Accordingly, the above-mentioned brokerage platform (400) can select the above-mentioned material information (i1) that has the same material type as the above-mentioned material information (I1). Of course, if there is no existing or multiple existing previously delivered material information (i1) that is identical in type to the above delivered material information (I1), additional items of the above delivered material data (DM) and previously delivered material data (dm) may be included to adjust the number of selected previously delivered material information (i1) to an appropriate level.In addition, the above-mentioned delivered material information (i1) additionally includes information regarding the delivery location among the above-mentioned delivered material data (dm) in order to pre-select the delivery company for the delivery of the above-mentioned required materials.

[0136] And the above brokerage platform (400) reads out delivery period information (I2), material unit price information (I3), and material quantity information (I4) from the above delivery material data (DM) and transmits them to the above supplier terminal (200) of the above material company that has pre-subscribed. Here, the delivery period information (I2) includes the delivery request date of the above required material, the material unit price information (I3) includes the estimated delivery price of the above required material, and the material quantity information (I4) includes the delivery quantity of the above required material.

[0137] In particular, in this embodiment, the intermediary platform (400) determines the priority of the quantified quality index, delivery time index, and cost index for the required materials based on the delivery material information (I1), delivery period information (I2), and material unit price information (I3) according to the type of required materials. And the intermediary platform (400) determines the priority

[0138] Accordingly, one of the above material companies that have made a provisional offer is selected as the order target. Additionally, the above brokerage platform (400) may classify the types of the above required materials into first to third materials (M1), (M2), and (M3). Here, the first material (M1) is selected as the order target among the above material companies that have made a provisional offer by evaluating in the order of the quality index, delivery index, and cost index; the second material (M2) is selected as the order target among the above material companies that have made a provisional offer by evaluating in the order of the quality index, cost index, and delivery index; and the third material (M3) is selected as the order target among the above material companies that have made a provisional offer by evaluating in the order of the cost index, delivery index, and quality index.

[0139] For example, the first material (M1) may include the hull, the second material (M2) may include engine fittings, and the third material (M3) may include hull fittings and cabin fittings. Accordingly, the intermediary platform (400) excludes from the ordering target any material company that has received a preliminary offer for the first and second materials (M1) (M2), even if the delivery time index and quality index are high, if the quality index is below a preset standard index. This is because, in the case of the first and second materials (M1) (M2), securing relatively high quality is required in relation to the operation or stability of the vessel; therefore, even if the delivery time or unit price is favorable, the material company that is concerned about a decline in quality is excluded from the ordering target. On the other hand, in the case of the first material (M1) mentioned above, since a delay in delivery during the ship construction process affects the assembly or installation of other materials, the material company whose scheduled delivery date exceeds the preset period compared to the requested delivery date is excluded from the ordering target. Additionally, in the case of the third material (M3) mentioned above, since it is less related to the operation or safety of the ship, the material company whose delivery unit price exceeds the preset ratio compared to the estimated delivery price is excluded from the ordering target.

[0140] Meanwhile, the above-mentioned user terminal (100) and supplier terminal (200) may be connected to the above-mentioned intermediary platform (400) via a network (500). Substantially, the above-mentioned network (500) refers to a connection structure capable of exchanging information between each node, such as the platform server (100) and the client terminal (200). Examples of the above-mentioned network (500) include a local area network (LAN), a wide area network (WAN), the World Wide Web (WWW), a wired and wireless data communication network, a telephone network, a wired and wireless television communication network, etc. Here, wireless data communication networks may include 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), 5GPP (5th Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), Wi-Fi, Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth network, NFC (Near-Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc.

[0141] Hereinafter, a method for delivering materials for ships according to an embodiment of the present invention will be described in more detail with reference to the attached drawings.

[0142] FIG. 11 is a flowchart showing a method for delivering materials for ships according to an embodiment of the present invention.

[0143] Referring to FIG. 11, a method for delivering materials for a ship according to an embodiment of the present invention may include a step of transmitting data of an ordered ship and delivered materials (S100), a step of reading information on materials already delivered (S200), a step of making a provisional offer for material delivery (S300), a step of accepting a provisional offer for material delivery (S400), a step of transmitting information on required materials (S500), a step of transmitting information on deliverable materials (S600), a step of determining a ranking of judgments (S700), a step of selecting an order target (S900), and a step of making a final offer for material delivery (S900).

[0144] More specifically, in the order vessel and delivery material data transmission step (S100), the user terminal (100) generates order vessel data (DS) regarding the order vessel and delivery material data (DM) regarding the required materials and transmits them to the intermediary platform (400). Then, in the delivery material information reading step (S200), the intermediary platform (400) selects one of the delivery vessel data (ds) that is closest to the order vessel data (DS) among the delivery vessel data (ds) stored in the database (300), and then reads the delivery material information (i1) from the delivery material data (dm) matched to the selected delivery vessel data (ds).

[0145] Next, in the material delivery provisional offer step (S300), the intermediary platform (400) reads out delivery material information (I1) from the delivery material data (DM), selects one or more of the previously delivered material information (i1) that are close to the delivery material information (I1), and makes a provisional offer for the delivery of the required material to the supplier terminal (200) held by the material company that is the delivery destination of the previously delivered material corresponding to the selected previously delivered material information (i1). At this time, it is preferable for the intermediary platform (400) to make a provisional offer for the delivery of the required material to two or more material companies. Additionally, in the provisional offer acceptance step (S400), the supplier terminal (200) accepts the provisional offer.

[0146] Meanwhile, in the above-mentioned material information transmission step (S500), the intermediary platform (400) reads out delivery period information (I2) including the delivery request date of the required material, material unit price information (I3) including the estimated delivery price of the required material, and material quantity information (I4) including the delivery quantity of the required material from the delivery material data (DM), and transmits them to the supplier terminal (200) of the material company that has pre-subscribed. Then, in the above-mentioned delivery availability information transmission step (S600), the supplier terminal (200) receives delivery deadline information (i2) including the estimated delivery date of the required material, delivery unit price information (i3) including the delivery unit price for the required material, and delivery quantity information (i4) including the delivery availability quantity of the required material, and transmits them to the intermediary platform (400).

[0147] In particular, in the present embodiment, in the judgment ranking determination step (S700), the brokerage platform (400) determines the priority of the quantified quality index, delivery date index, and cost index for the required materials based on the delivery material information (I1), delivery deadline information (I2), and material unit price information (I3) according to the material type of the required materials. In the above judgment ranking determination step (S700), the brokerage platform (400) may select the order target among the material companies that have pre-subscribed by evaluating the first material (M1), which includes the hull, in the order of the quality index, delivery index, and cost index; select the order target among the material companies that have pre-subscribed by evaluating the second material (M2), which includes the engine fittings, in the order of the quality index, cost index, and delivery index; and select the order target among the material companies by evaluating the third material (M3), which includes the hull fittings and cabin fittings, in the order of the cost index, delivery index, and quality index. At this time, the above brokerage platform (400) may exclude from the ordering target any material company among the material companies that have received a preliminary offer for the first and second materials (M1) (M2) that has a quality index lower than a preset standard index, and in the case of the first material (M1), exclude from the ordering target any material company among the material companies that have received a preliminary offer that has a delivery scheduled date exceeding a preset period compared to the delivery request date, and in the case of the third material (M3), exclude from the ordering target any material company among the material companies that have received a preliminary offer that has a delivery unit price exceeding a preset ratio compared to the delivery estimated price.

[0148] And in the order target selection step (S800), the brokerage platform (400) selects one of the material companies that have made a provisional offer according to the priority as the order target. In the material delivery main offer step (S900), the user terminal (100) makes a main offer for the delivery of the required materials to the material company selected as the order target through the brokerage platform (400).

[0149] The scope of the present invention is defined by the claims set forth below rather than by the detailed description above, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present invention.

Claims

1. (a) generating an initial chromosome population comprising an initial chromosome having an initial gene composed of a supplier and an allocation of said supplier; (b) a step of evaluating each chromosome of the initial chromosome population using an objective function; (c) A step of selecting the evaluated chromosomes as parental chromosomes according to fitness; (d) a step of generating offspring chromosomes by applying mutations to the selected parent chromosomes; (e) a step of updating the parent chromosomes by replacing the parent chromosomes of step (c) with the offspring chromosomes; (f) checking whether the fitness of the updated parental chromosomes is satisfied, and if not, repeating steps (b), (c), (d) and (e) until the fitness is satisfied; and (g) a step of outputting a final chromosome including a final supplier and an allocation that satisfy the above suitability; Optimization method for supplier selection and volume allocation including 2. In Paragraph 1, An optimization method characterized in that the initial chromosome of step (a) is represented as a two-dimensional matrix including a supplier and the allocation amount of said supplier.

3. In Paragraph 1, An optimization method characterized in that the objective function of step (b) is represented by Equation 1. [Equation 1] In the above Equation 1, And, The above α is a weighting factor assigned to the price of the component provided by the supplier, and The above β is a weighting factor assigned to the manufacturing time of the component provided by the supplier, and The above γ is a weighting factor assigned to the demand for components provided by the supplier, and And, And, And, is the ratio of each component allocated to the selected supplier, and N is the total number of suppliers (i: supplier index), and M is the total number of components (j: component index), and P ij is the price of the j-th component provided by the i-th supplier, and T ij is the manufacturing time of the j-th component at the i-th supplier, and D j is the demand for the j-th component, and B j is the budget of the j-th component, and Cap ij is the capacity of the i-th vendor for the j-th component, and PC ij is the process capability (%) of the i-th vendor for the j-th component.

4. In Paragraph 1, An optimization method characterized in that, in step (b), the evaluation using the objective function is performed using one or more selected from the group consisting of Z-transform and linear scaling.

5. In Paragraph 4, An optimization method characterized in that the above Z-transform is performed using the following Equation 2. [Equation 2] In the above Equation 2, is a representative value of the 2-D matrix chromosome, and is the mean value of the representative values ​​of the 2-D matrix chromosomes, and is the standard deviation value of the representative value of the 2-D matrix chromosome.

6. In Paragraph 5, An optimization method characterized in that the above linear scaling is performed using the following Equation 3. [Equation 3] In the above Equation 3, Is It is a representative value of the 2-D matrix chromosome, and Is It is the minimum value of the representative value of the 2-D matrix chromosome, and is the maximum value of the representative value of the 2-D matrix chromosome, and a and b are scale constants, respectively, and 0 ≤ a ≤ 1 and, 0 ≤ b ≤ 1.

7. In Paragraph 1, An optimization method characterized by using a fitness proportionate selection mechanism in step (c) to assign fitness values ​​to each chromosome and selecting parent chromosomes according to the magnitude of the fitness values.

8. In Paragraph 1, Step (d) (d-1) A step of introducing row-based crossover on the selected parent chromosomes; (d-2) a step of introducing random mutations into parent chromosomes into which the row-based crossover has been introduced; and (d-3) A step of generating offspring chromosomes by performing local improvement on parent chromosomes into which the above random mutations have been introduced; an optimization method characterized by including 9. In Paragraph 8, An optimization method characterized by performing row-based crossover in step (d-1) with a crossover rate of 60 to 80%.

10. In Paragraph 8, An optimization method characterized by introducing random mutations in step (d-2) at a mutation rate of 0.06 to 0.14%.

11. In Paragraph 8, An optimization method characterized by performing local improvement in step (d-3) using a 2-swap mechanism and repeating the 2-swap until the best fit is obtained.

12. In Paragraph 11, An optimization method characterized by the above 2-swap mechanism being performed by controlling the number of swaps of parent chromosomes and the row selection probability.

13. In Paragraph 1, An optimization method characterized in that, in step (e), the fitness calculation of the parent chromosome population is performed through a selection method.

14. In Paragraph 1, The above optimization method is intended to be used for supplier selection and volume allocation in a ship material delivery system, and The above ship material delivery system A ship material delivery system comprising: a user terminal (100) held by a ship company that builds an ordered ship; a supplier terminal (200) each held by a plurality of material companies that supply materials required for the construction of the ordered ship; a database (300) in which data on previously built ships (ds) built by the ship company and data on previously supplied materials (dm) used in the construction of the previously built ships are matched and stored; and a mediation platform (400) that mediates the delivery of materials required for the ordered ship between the user terminal (100) and the supplier terminal (200): The above user terminal (100) is, Order ship data (DS) regarding the order ship and delivery material data (DM) regarding the required materials are generated and transmitted to the intermediary platform (400), and The above supplier terminal (200) is, Accepting a provisional offer for the delivery of the required materials to the user terminal (100) through the above brokerage platform (400), and Delivery deadline information (i2) including the expected delivery date of the above-mentioned required materials, delivery unit price information (i3) including the delivery unit price for the above-mentioned required materials, and delivery quantity information (i4) including the available delivery quantity of the above-mentioned required materials are transmitted to the above-mentioned intermediary platform (400). The above brokerage platform (400) is, Select one of the above-mentioned built-up ship data (ds) that is closest to the above-mentioned order ship data (DS), and read out at least one piece of information on previously delivered materials (i1) including the material type and delivery location of the previously delivered materials from the above-mentioned delivered material data (dm) matched thereto, and From the above delivery material data (DM), delivery material information (I1) including at least the material type of the above delivery material is read out, and one or more of the above previously delivered material information (i1) that are close to the above delivery material information (I1) are selected, and a provisional order for the delivery of the above required material is made to the above supplier terminal (200) held by the above material company, which is the delivery destination of the above previously delivered material corresponding to the selected above previously delivered material information (i1). Delivery period information (I2) including the delivery request date of the required material, material unit price information (I3) including the estimated delivery price of the required material, and material quantity information (I4) including the delivery quantity of the required material are read from the above delivery material data (DM) and transmitted to the above supplier terminal (200) of the above material company that has pre-registered. Based on the material type of the above required material, the priority of the quantified quality index, delivery date index, and cost index for the above required material is determined based on the above delivery material information (I1), delivery deadline information (I2), and material unit price information (I3). An optimization method characterized by a ship material delivery system that selects one of the aforementioned material companies that have received an offer as the order target according to the above priority.

15. In Paragraph 14, The types of materials required above are, A first material (M1) that selects the order target among the material companies that have received a preliminary offer by evaluating in the order of the quality index, delivery index, and cost index; A second material (M2) that selects the order target among the material companies that have received a preliminary offer by evaluating in the order of the quality index, cost index, and delivery index; and An optimization method characterized by including a third material (M3) that selects the order target among the material companies that have received a preliminary offer by evaluating in the order of the cost index, delivery index, and quality index.

16. In Paragraph 15, The above first material (M1) includes a hull, and The above second material (M2) includes institutional fittings, and An optimization method characterized in that the above third material (M3) includes hull fittings and cabin fittings.

17. In Paragraph 15, The above brokerage platform (400) is, In the case of the above first and second materials (M1)(M2), among the material companies that have made a provisional offer, the material companies whose quality index is below the preset standard index are excluded from the ordering target. In the case of the above first material (M1), among the above material companies that have made a provisional offer, the above material company whose scheduled delivery date exceeds the pre-set period compared to the above delivery request date is excluded from the above order target, and An optimization method characterized by excluding from the ordering target any material company among the material companies that have received a preliminary offer for the above third material (M3) that has a delivery unit price exceeding a predetermined ratio compared to the above expected delivery price.

18. In Paragraph 14, The above optimization method is intended to be used for supplier selection and volume allocation of the ship material delivery method by the ship material delivery system, and The above method for supplying ship materials is, A step (S100) in which the above-mentioned user terminal (100) generates order ship data (DS) regarding the order ship and delivery material data (DM) regarding the required materials and transmits them to the above-mentioned intermediary platform (400); A pre-delivered material information reading step (S200) in which the above-described brokerage platform (400) selects one of the above-described built ship data (ds) closest to the above-described order ship data (DS), and reads out at least one pre-delivered material information (i1) including the material type and delivery location of the pre-delivered material from the above-described pre-delivered material data (dm) matched thereto; A material delivery provisional application step (S300) in which the above-mentioned brokerage platform (400) reads out delivery material information (I1) including at least the material type of the delivery material from the above-mentioned delivery material data (DM), selects one or more of the above-mentioned delivery material information (i1) that are close to the above-mentioned delivery material information (I1), and provisionally applies for the delivery of the required material to the above-mentioned supplier terminal (200) held by the above-mentioned material company that is the delivery destination of the above-mentioned delivery material corresponding to the selected above-mentioned delivery material information (i1); The above supplier terminal (200) accepts the above material delivery offer acceptance step (S400); A step of transmitting required material information (S500) in which the above brokerage platform (400) reads out delivery period information (I2) including the delivery request date of the required material, material unit price information (I3) including the estimated delivery price of the required material, and material quantity information (I4) including the delivery quantity of the required material from the above delivery material data (DM), and transmits them to the supplier terminal (200) of the above material company that has pre-registered; A delivery availability information transmission step (S600) in which the above supplier terminal (200) receives delivery deadline information (i2) including the expected delivery date of the above required material, delivery unit price information (i3) including the delivery unit price for the above required material, and delivery quantity information (i4) including the delivery quantity of the above required material, and transmits them to the above brokerage platform (400); The above-mentioned brokerage platform (400) determines the priority of a quantified quality index, delivery date index, and cost index for the above-mentioned required material based on the delivery material information (I1), delivery deadline information (I2), and material unit price information (I3) according to the material type of the above-mentioned required material, in a judgment ranking determination step (S700); and An optimization method characterized by including: a step (S800) in which the above brokerage platform (400) selects one of the above material companies that have received a preliminary offer according to the above priority as the order target.

19. In Paragraph 18, In the above judgment ranking determination step (S700), The above brokerage platform (400) is, The above required materials, The first material (M1), including the hull, is evaluated in the order of the quality index, delivery index, and cost index, and the ordering target is selected from among the material companies that have received a preliminary offer. The second material (M2), including the institutional equipment, is selected from among the material companies that have received a preliminary offer by evaluating the quality index, cost index, and delivery index in that order, and the order target is selected. An optimization method characterized by selecting the order target among the material companies by evaluating the third material (M3), including hull outfitting and cabin outfitting, in the order of the cost index, delivery index, and quality index.

20. In Paragraph 19, In the above order target selection step (S800), The above brokerage platform (400) is, In the case of the above first and second materials (M1)(M2), among the material companies that have made a provisional offer, the material companies whose quality index is below the preset standard index are excluded from the ordering target. In the case of the above first material (M1), among the above material companies that have made a provisional offer, the above material company whose scheduled delivery date exceeds the pre-set period compared to the above delivery request date is excluded from the above order target, and An optimization method characterized by excluding from the ordering target any material company among the material companies that have received a preliminary offer for the above third material (M3) that has a delivery unit price exceeding a predetermined ratio compared to the above expected delivery price.

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