A Multi-Objective-Based Evaluation Method and System for Production Scheduling Schemes
By converting the optimization objective of production scheduling into soft and hard constraints, and utilizing configuration coefficients and importance weights, the problems of shop floor deviation and differences in the magnitude of optimization objectives in production scheduling are solved, thus realizing the feasibility and optimization effect of the scheduling scheme.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI BAOSIGHT SOFTWARE CO LTD
- Filing Date
- 2021-10-21
- Publication Date
- 2026-07-31
AI Technical Summary
Existing production scheduling software in enterprise production scenarios suffers from significant deviations between workshop production schedules and actual performance, and fails to effectively handle the magnitude differences between different optimization objectives and the problem of invalid weight configurations.
The optimization objectives of production scheduling are converted into soft constraints, and the constraints in business processes are converted into hard constraints. The evaluation impact of hard and soft constraints is distinguished by configuration coefficients and importance weights. The total penalty score is calculated using standardized processing to ensure the feasibility and optimization effect of the scheduling scheme.
It enables the effective differentiation and weight allocation of objectives while meeting constraints, thereby improving the feasibility and adaptability of production scheduling schemes and meeting different business needs.
Smart Images
Figure CN116011839B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of production scheduling scheme evaluation technology, and more specifically, to a method and system for evaluating production scheduling schemes based on multiple objectives. Background Technology
[0002] Existing enterprise complex production system planning and scheduling generally adopts advanced production scheduling (APS) software. The APS software available on the market performs data modeling based on the product bill of materials (BOM), resources, processes, calendars, constraints, etc. in the enterprise production scenario, and generates planning orders or work orders based on the input master production schedule, which are then directly issued to the workshop for execution. This may result in a large deviation between the workshop production schedule and the actual execution, which poses a significant risk to normal production organization and affects the production organization progress. Therefore, it is necessary to conduct a feasibility assessment of the production scheduling scheme.
[0003] While existing technologies (such as Chinese patent application number CN201811618993.3, which discloses "a scheduling method and system for power metering devices based on genetic algorithms") provide evaluation indicators for scheduling schemes, they do not consider the magnitude differences between various optimization objectives and directly assign weight ratios to different optimization objectives. If the fitness values of various optimization objectives are not on the same order of magnitude, the scheduling scheme cannot adjust the results according to the manually set weight values, even if the weights of the objectives are manually configured.
[0004] Patent document CN101261702A (application number: CN200810035773.8) discloses a scheduling scheme evaluation and selection method based on layer-by-layer optimization. This method employs the idea of layer-by-layer optimization, that is, performing multi-level evaluations of the obtained scheduling schemes based on constraints, primary optimization objectives, and secondary optimization objectives to achieve multi-objective optimization. During the evaluation process, the obtained scheduling schemes are evaluated through constraint checks and fitness calculations, ultimately outputting the scheduling scheme with the fewest constraints violations as the optimal scheduling scheme. However, this patent does not address the problem of large differences in the magnitude of penalty values for different constraints, nor does it solve the problem of invalid user-configured weights due to these large differences in magnitude. Summary of the Invention
[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for evaluating production scheduling schemes based on multiple objectives.
[0006] The multi-objective-based production scheduling scheme evaluation method provided by the present invention includes:
[0007] Step 1: Convert the optimization objective of production scheduling into soft constraints;
[0008] Step 2: Convert the constraints in the business process into hard constraints;
[0009] Step 3: For a production scheduling plan, iterate through each constraint i, which includes soft constraints and hard constraints. Within each constraint i, iterate through each order j in the production scheduling order and calculate the penalty value of order j on constraint i. And save the record;
[0010] Step 4: Calculate the total penalty score of the production scheduling plan and evaluate the production scheduling plan based on the total penalty score.
[0011] Preferably, at the end of the traversal of each constraint i, if If the value is not 0, it is standardized using the following formula:
[0012]
[0013] Preferred, based on standardized processing The total penalty value on constraint i is calculated using the following formula:
[0014]
[0015] Preferably, if constraint i is a hard constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ1, where λ1 = 1000 is the configuration coefficient;
[0016] If constraint i is a soft constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ2, where λ2 = 1 is the allocation coefficient;
[0017] By configuring coefficients, hard constraint optimization is given higher priority and has a much greater impact on the evaluation of production scheduling schemes than soft constraints, thus ensuring that the production scheduling scheme is a feasible solution.
[0018] For soft constraints, importance weights α are configured based on the user's actual production needs. i Update the total penalty value cost on soft constraint i. i '=cost i *α i If no importance weight is configured, all optimization objectives are assumed to be of equal importance.
[0019] Preferably, the total penalty score for the production scheduling plan is calculated using the following formula:
[0020] cost = sum(cost) i ')
[0021] The lower the total penalty score (cost), the better the production scheduling plan.
[0022] The multi-objective-based production scheduling scheme evaluation system provided by the present invention includes:
[0023] Module M1: Converts the optimization objective of production scheduling into soft constraints;
[0024] Module M2: Converts constraints in the business process into hard constraints;
[0025] Module M3: For a production scheduling plan, it iterates through each constraint i, which includes soft constraints and hard constraints. Within each constraint i, it iterates through each order j in the production scheduling order and calculates the penalty value of order j on constraint i. And save the record;
[0026] Module M4: Calculates the total penalty score for the production scheduling plan and evaluates the production scheduling plan based on the total penalty score.
[0027] Preferably, at the end of the traversal of each constraint i, if If the value is not 0, it is standardized using the following formula:
[0028]
[0029] Preferred, based on standardized processing The total penalty value on constraint i is calculated using the following formula:
[0030]
[0031] Preferably, if constraint i is a hard constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ1, where λ1 = 1000 is the configuration coefficient;
[0032] If constraint i is a soft constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ2, where λ2 = 1 is the allocation coefficient;
[0033] By configuring coefficients, hard constraint optimization is given higher priority and has a much greater impact on the evaluation of production scheduling schemes than soft constraints, thus ensuring that the production scheduling scheme is a feasible solution.
[0034] For soft constraints, importance weights α are configured based on the user's actual production needs. i Update the total penalty value cost on soft constraint i. i '=cost i *α i If no importance weight is configured, all optimization objectives are assumed to be of equal importance.
[0035] Preferably, the total penalty score for the production scheduling plan is calculated using the following formula:
[0036] cost = sum(cost) i ')
[0037] The lower the total penalty score (cost), the better the production scheduling plan.
[0038] Compared with the prior art, the present invention has the following beneficial effects:
[0039] (1) By adopting standardized operations, this invention solves the problem of large differences in the magnitude of penalty values for different constraints, and further solves the problem of invalid weights configured by users due to large differences in magnitude;
[0040] (2) By assigning coefficients to hard constraints and soft constraints respectively, this invention distinguishes the degree of evaluation of scheduling schemes by hard constraints (constraint conditions) and soft constraints (optimization objectives). On the basis of satisfying the constraints, the optimization objective is then optimized.
[0041] (3) This invention solves the problem that scheduling schemes under different business needs focus on different objectives by supporting users to configure the weight of optimization objectives. Attached Figure Description
[0042] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:
[0043] Figure 1 A flowchart for evaluating the model design is provided. Detailed Implementation
[0044] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.
[0045] Example:
[0046] This invention provides a method for designing an evaluation model for production scheduling schemes, which is used to evaluate the advantage of a scheduling scheme in production scheduling and is applicable to large-scale production scheduling with multiple optimization objectives and multiple production constraints.
[0047] In the process of optimizing production scheduling schemes, when multiple scheduling schemes exist, it is necessary to select candidate schemes. The evaluation model serves as the standard for selecting scheduling schemes, such as... Figure 1The design method of the evaluation model in this invention is as follows:
[0048] Step 1: Analyze the optimization goals of the production schedule: such as meeting order delivery deadlines, reducing the frequency of process changeovers during production, and increasing production capacity.
[0049] Step 2: Review the constraints in the business process: such as the requirement that batch orders must meet a certain minimum quantity, or that a certain transition period is needed before high-quality products can be produced.
[0050] Step 3: Since the constraints must be met, they can be converted into hard constraints. The scheduling objective is to optimize as much as possible, so it can be converted into soft constraints.
[0051] Step 4: For a production scheduling plan, iterate through each constraint i (soft and hard constraints). Within each constraint, iterate through each order j in the scheduling order and calculate the penalty value of order j on constraint i. And save the record. cost i The settings can be customized according to the business scenario of each constraint.
[0052] Step 5: When each constraint ends its traversal, if If the value is not 0, then standardization is performed:
[0053]
[0054] Step Six: For the standardized calculate
[0055] Step 7: If constraint i is a hard constraint, the configuration coefficient λ1 = 1000, and the cost... i =cost i *λ1; If constraint i is a soft constraint, the allocation coefficient λ2 = 1, cost i =cost i *λ2. The role of the configuration coefficient λ is to ensure that hard constraint optimization has a higher priority and its impact on the evaluation of scheduling schemes is far greater than that of soft constraints, ensuring that the scheme is a feasible solution.
[0056] Step 8: For soft constraints (optimization objectives), configure importance weights α according to the user's actual production needs. i cost i =cost i *α i If no importance weights are configured, all optimization objectives are assumed to be of equal importance.
[0057] Step 9: Calculate the total cost of the scheduling plan: cost = sum(cost) iThe smaller the cost value, the better the scheduling scheme.
[0058] The production scheduling scheme evaluation system based on multi-objectives provided by the present invention includes: module M1: converting the optimization objective of production scheduling into soft constraints; module M2: converting the constraints in the business process into hard constraints; module M3: for a production scheduling scheme, traversing each constraint i, wherein the constraint i includes soft constraints and hard constraints, and within each constraint i, traversing each order j according to the production scheduling order, and calculating the penalty value of order j on constraint i. And save the record; Module M4: Calculate the total penalty score of the production scheduling plan and evaluate the production scheduling plan based on the total penalty score.
[0059] When the traversal ends at each constraint i, if If the value is not 0, it is standardized using the following formula: Based on standardized processing The total penalty value on constraint i is calculated using the following formula: If constraint i is a hard constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ1, where λ1 = 1000 is the configuration coefficient; if constraint i is a soft constraint, then the optimized total penalty value cost on constraint i is... i '=cost i *λ2, where λ2 = 1 is the configuration coefficient; the configuration coefficient ensures that hard constraint optimization has a higher priority and its impact on the evaluation of the production scheduling scheme is much greater than that of soft constraints, ensuring that the production scheduling scheme is a feasible solution; for soft constraints, importance weights α are configured according to the user's actual production needs. i Update the total penalty value cost on soft constraint i. i '=cost i *α i If no importance weights are configured, all optimization objectives are assumed to be of equal importance. The total penalty score for the production scheduling plan is calculated using the formula: cost = sum(cost / sigma). i The smaller the total penalty score (cost), the better the production scheduling plan.
[0060] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.
[0061] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.
Claims
1. A multi-objective based production scheduling scheme evaluation method, characterized by, include: Step 1: Convert the optimization goals of production scheduling into soft constraints. The optimization goals include meeting order delivery deadlines, reducing the frequency of process changeovers during production, and increasing capacity. Step 2: Convert the constraints in the business process into hard constraints. These constraints include the requirement that order batches must meet a certain minimum quantity and that a certain transition period is required before high-quality products can be produced. Step 3: For a production scheduling plan, iterate through each constraint i, which includes soft constraints and hard constraints. Within each constraint i, iterate through each order j in the production scheduling order and calculate the penalty value of order j on constraint i. And save the record; Step 4: Calculate the total penalty score for the production scheduling plan and evaluate the production scheduling plan based on the total penalty score; When the traversal ends at each constraint i, if If the value is not 0, it is standardized using the following formula: Based on standardized processing The total penalty value on constraint i is calculated using the following formula: If constraint i is a hard constraint, then the total penalty value on constraint i after optimization is... , For configuration coefficients; If constraint i is a soft constraint, then the total penalty value on constraint i after optimization is... , For configuration coefficients; By configuring coefficients, hard constraint optimization is given higher priority and has a much greater impact on the evaluation of production scheduling schemes than soft constraints, thus ensuring that the production scheduling scheme is a feasible solution. For soft constraints, importance weights are then configured based on the user's actual production needs. Update the total penalty value on soft constraint i. If no importance weight is configured, all optimization objectives are assumed to be of equal importance.
2. The multi-objective-based production scheduling scheme evaluation method according to claim 1, characterized in that, The total penalty score for calculating the production scheduling plan is calculated using the following formula: The lower the total penalty score (cost), the better the production scheduling plan.
3. A production scheduling scheme evaluation system based on multiple objectives, characterized in that, The production scheduling scheme evaluation method based on multiple objectives as described in claim 1 includes: Module M1: Converts the optimization goals of production scheduling into soft constraints. The optimization goals include meeting order delivery deadlines, reducing the frequency of process changeovers during production, and increasing capacity. Module M2: Converts the constraints in the business process into hard constraints. These constraints include the requirement that order batches must meet a certain minimum quantity and that a certain transition period is required before products with high quality requirements can be produced. Module M3: For a production scheduling plan, it iterates through each constraint i, which includes soft constraints and hard constraints. Within each constraint i, it iterates through each order j in the production scheduling order and calculates the penalty value of order j on constraint i. And save the record; Module M4: Calculates the total penalty score for a production scheduling plan and evaluates the production scheduling plan based on the total penalty score; When the traversal ends at each constraint i, if If the value is not 0, it is standardized using the following formula: Based on standardized processing The total penalty value on constraint i is calculated using the following formula: If constraint i is a hard constraint, then the total penalty value on constraint i after optimization is... , For configuration coefficients; If constraint i is a soft constraint, then the total penalty value on constraint i after optimization is... , For configuration coefficients; By configuring coefficients, hard constraint optimization is given higher priority and has a much greater impact on the evaluation of production scheduling schemes than soft constraints, thus ensuring that the production scheduling scheme is a feasible solution. For soft constraints, importance weights are then configured based on the user's actual production needs. Update the total penalty value on soft constraint i. If no importance weight is configured, all optimization objectives are assumed to be of equal importance.
4. The multi-objective production scheduling scheme evaluation system according to claim 3, characterized in that, The total penalty score for calculating the production scheduling plan is calculated using the following formula: The lower the total penalty score (cost), the better the production scheduling plan.