Planning system, planning method, and program

Abstract

To provide a planning system, method and program for planning cargo arrangement so as to prevent rehandling as possible during carrying out cargo even if future cargo carry-in schedule is unfixed.SOLUTION: In a planning system 10, a location determination unit 123 calculates a location of second cargo based on probability distribution information indicating a relationship between cargo carry-out priority and occurrence probability, information on cargo already placed and carry-out schedule of the cargo, and an evaluation formula which calculates a difference between a first evaluation value and a second evaluation value, the first evaluation value being obtained by calculating, including cargo to be carried in after first cargo and placed, based on probability distribution information, evaluation values of the number of tasks to move other cargo for carrying out the first cargo to be generated due to the arrangement of the first cargo, the second evaluation value being obtained by calculating, including cargo to be carried in after second cargo, based on the probability distribution information, evaluation values of the number of tasks to be generated due to the arrangement of the second cargo which is to be carried in after the first cargo and placed.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a planning system, a planning method, and a program. [Background technology]

[0002] Patent Document 1 discloses a technology that predicts the date and order of removal of each container based on performance information of containers that have been unloaded and carried out at a container terminal in the past, and determines the storage location of each container so as to satisfy a specified evaluation index to reduce as much as possible the reshuffling work associated with the removal of each container, based on constraints related to container placement that promote the efficiency of loading and unloading work.The technology in Patent Document 1 is a technology that, when the order of containers being brought in is fixed, predicts the order of removal and places containers so as to prevent reshuffling at the time of removal, but it is unclear whether it can prevent reshuffling when the order of containers being brought in is changed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2022 / 013966 Summary of the Invention [Problem to be solved by the invention]

[0004] Even when future container delivery schedules are uncertain, a technology is needed to create a layout plan that minimizes the need for rearrangements.

[0005] The present disclosure provides a planning system, a planning method, and a program that can solve the above problems. [Means for solving the problem]

[0006] The planning system of the present disclosure includes probability distribution information indicating the relationship between the removal priority of a package and the probability of the package occurring, information on package items already placed at a placement location and the planned removal of the package, an evaluation formula for calculating the difference between a first evaluation value calculated based on the probability distribution information to evaluate the number of tasks required to move other package items to remove the first package, which will be generated by placing a first package at the placement location, including package items that will be brought in after the first package and placed at the placement location, and a second evaluation value calculated based on the probability distribution information to evaluate the number of tasks required by placing a second package at the placement location, which will be brought in after the second package, including package items that will be brought in after the second package, and a placement location determination unit that calculates the placement location of the second package based on the evaluation formula.

[0007] In addition, the planning method of the present disclosure calculates the placement location of the second luggage based on information on luggage already placed at the placement location and the scheduled removal of the luggage, and an evaluation formula that calculates the difference between a first evaluation value calculated based on probability distribution information showing the relationship between the luggage removal priority and the occurrence probability of the luggage, and an evaluation value of the work of moving other luggage to remove the first luggage that occurs when the first luggage is placed at the placement location, including luggage that will be brought in after the first luggage and placed at the placement location, and a second evaluation value calculated based on the probability distribution information, including luggage that will be brought in after the second luggage and placed at the placement location, that occurs when the second luggage is placed at the placement location, and

[0008] In addition, the program disclosed herein causes a computer to execute a process of calculating the placement location of a second piece of luggage based on information on luggage already placed at a placement location and the scheduled removal of the luggage, and an evaluation formula that calculates the difference between a first evaluation value calculated based on probability distribution information showing the relationship between the removal priority of the luggage and the occurrence probability of the luggage, and an evaluation value of the work of moving other luggage to remove the first piece of luggage that occurs when the first piece of luggage is placed at the placement location, including luggage that will be brought in after the first piece of luggage and placed at the placement location, and a second evaluation value calculated based on the probability distribution information, including luggage that will be brought in after the second piece of luggage and placed at the placement location, that occurs when a second piece of luggage that will be brought in after the first piece of luggage is placed at the placement location. [Effects of the Invention]

[0009] According to the above-described planning system, planning method, and program, even if the future cargo delivery schedule is uncertain, it is possible to plan the placement of cargo so as to minimize cargo rearrangement when the cargo is delivered. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram illustrating an example of a planning system according to an embodiment. [Figure 2A] FIG. 1 is a first diagram showing an example of a location where luggage is placed according to an embodiment. [Figure 2B] FIG. 2 is a second diagram showing an example of a location where luggage is placed according to the embodiment. [Figure 3] 10A and 10B are diagrams illustrating a method for calculating a placement location of luggage according to an embodiment. [Figure 4] FIG. 10 is a diagram illustrating an example of the occurrence probability of reordering according to the embodiment. [Figure 5] 10 is a flowchart illustrating an example of a plan creation process according to the embodiment. [Figure 6] FIG. 1 is a diagram illustrating an example of a hardware configuration of a planning system according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] <Embodiment> The planning system according to each embodiment will be described in detail below with reference to FIGS. (composition) 1 is a block diagram showing an example of a planning system according to an embodiment of the present invention. In this embodiment, the planning system is configured with a computer device such as a single PC or a server device. In a situation where cargo delivered to a container terminal or the like at a port is to be stored in a storage location, and it is uncertain what cargo will be delivered in the future, the planning system 10 creates a cargo placement plan that includes cargo to be delivered in the future and minimizes the number of cargo handling operations.

[0012] As shown in FIG. 1, the planning system 10 includes a data acquisition unit 11, a planning unit 12, an output unit 13, and a storage unit 14. The data acquisition unit 11 acquires information necessary for creating a luggage placement plan, such as information on the layout of the luggage storage area, information on luggage to be removed and inventory information (where and what size, weight and type of luggage is placed), data showing the probability distribution of removal priority, test data used to adjust the parameters described below, and information on the type of luggage that is required to be placed (luggage to be brought in), and writes and records this information in the memory unit 14.

[0013] The planning unit 12 creates an optimal storage plan for luggage. The planning unit 12 includes a parameter setting unit 121, an evaluation formula definition unit 122, and a placement location determination unit 123. The parameter setting unit 121 performs a simulation of loading and unloading using the test data acquired by the data acquisition unit 11, evaluates what values ​​of the parameters of the evaluation formula described later can reduce the number of times of handling, and sets values ​​of the parameters that can reduce the number of times of handling. The evaluation formula definition unit 122 defines an evaluation formula for evaluating the increase in the number of times of rearrangement when the delivered cargo is placed at a certain location. The placement location determination unit 123 calculates the placement location of the luggage that minimizes the value of the evaluation formula defined by the evaluation formula definition unit 122.

[0014] The output unit 13 outputs the placement locations of the luggage obtained by the placement location determination unit 123 through the optimization calculation. The storage unit 14 stores various information necessary for creating an optimal luggage placement plan.

[0015] (Luggage placement location configuration) 2A and 2B are first and second diagrams, respectively, illustrating an example of a luggage placement location according to an embodiment. FIG. 2A shows a plan view of the luggage placement location. FIG. 2B shows a cross-sectional view of the placement location. Lanes 30 represent a set of luggage placement locations divided by the operating range of materials handling equipment 20, the type of equipment, and the like. While FIG. 2A shows one lane 30, there may be multiple lanes 30, or the lane 30 in FIG. 2A may be divided into, for example, two lanes, 30A and 30B, each of which may be treated as a separate lane. Lanes 30 are, for example, a set of locations where movement can be avoided without crossing the path of conveying equipment (such as vehicles carrying luggage to a container terminal). Materials handling equipment 20 places luggage carried into a loading entrance 31 in one of lanes 30 while moving in the horizontal direction (row direction) of the page. Materials handling equipment 20 also transports luggage placed in lanes 30 to an exit 32. A bay 40 represents a set of locations where loading and unloading operations can be performed while the material handling equipment 20 is parked. Each column of the lanes 30, which are divided into a matrix in FIG. 2A, represents a bay 40. A row 50 represents a set of locations where cargo can be packed in one direction. Each cell in FIG. 2A represents a row 50. As shown in FIG. 2B, cargo can be loaded and unloaded in a stacked format in a row 50. In a row 50, cargo such as containers is stacked vertically on the page. One row 50 includes multiple locations 60. Each location 60 is a location where cargo is placed. One cargo can be placed in one location 60. For example, suppose that cargo is placed in locations 60-1 and 60-2 in FIG. 2B, and the cargo at location 60-2 needs to be loaded first. In this case, the cargo at location 60-1 must be moved to another location to remove the cargo from location 60-2. This process of temporarily moving other items placed closer to the outgoing entrance 32 to another location is called relocation. The planning system 10 creates a plan for arranging items brought into the lane 30 by searching for an arrangement location 60 that minimizes the number of relocations. Here, it is assumed that the outgoing schedule for items (when, which items, and in what order to take out and ship) is determined, but the incoming schedule is not determined, or even if it is determined, it may change.In other words, the system determines the placement locations of the cargoes that are being brought in one after another when the cargo delivery schedule is not yet confirmed, calculating how to arrange the cargoes so that they can be delivered while preventing rearrangements in relation to the confirmed delivery schedule.

[0016] 2A and 2B show an example in which parcels are stored in stacks in rows 50 (rows are also referred to as lists), but the parcel placement planning method of this embodiment, which minimizes the number of times parcels are moved, can also be used when parcels are stored in queues. Furthermore, the parcel delivery and delivery in this embodiment are based on the premise that the delivery period and delivery period are completely separate. For example, suppose parcels are delivered between time T1 and time T2, and the parcels delivered during that time period are delivered between time T3 and time T4, which is a time period after time T2. When the delivery and delivery periods are separate, it is only necessary to consider that the delivery times of the parcels are not reversed relative to the location of the parcels relative to the delivery entrance 32.

[0017] Next, a method for calculating the placement location of a package will be described with reference to FIG. 3. FIG. 3 shows a cross section of a certain bay 40. The bay 40 includes rows 50-1 to 50-5. Here, a specific bay 40 is limited to be a bay in the lane 30 where a newly carried-in package x is placed, and a row 50 within the limited bay 40 is considered to reduce the number of times package x should be loaded. Other packages have already been placed in the shaded areas of rows 50-1 to 50-5. Therefore, when placing package x, a placement location that will minimize the number of times package x should be loaded must be selected from placement locations 60-1 to 60-5.

[0018] Here, in order to minimize the number of times that handling operations increase due to the placement of luggage, an evaluation formula is introduced that evaluates the predicted increase in the number of times that handling operations will occur using the probability of future luggage occurrence. Evaluation formula (1) is shown below.

[0019]

number

[0020] Let x be the luggage to be placed, and l be the list (row) where it will be placed. The evaluation value of the number of reversals when a certain luggage x is placed on a certain list l can be expressed by the above evaluation formula (1). The first term h1(x, l) in formula (1) indicates the number of reversals (number of reversals) with luggage that is currently already placed on list l. The second and third terms (h2(x, l)-h3(x, l)) in formula (1) indicate the number of reversals expected in the future. α is a parameter that indicates how much the number of reversals expected in the future depends on probability. α is set by experimentally estimating the degree to which the number of reversals that actually occur will be reduced. Each term will be explained in more detail.

[0021] The first term represents the total number of items that have been swapped with x1 already placed in list l. If y is a variable that indicates whether x1 has been swapped with x using 0 or 1, and the set of items in the list is XinList, then the first term of evaluation formula (1) can be expressed as the following formula (2).

[0022]

number

[0023] For example, when placing package x at location 60-1, if the package already placed in row 50-1 is scheduled to be removed first, the value of equation (2) is 1, and if package x is scheduled to be removed first, the value of equation (2) is 0. Similarly, when placing package x at location 60-2, if two packages already placed in row 50-2 are scheduled to be removed before package x, the value of equation (2) is 2, and if only one of the two packages is scheduled to be removed before package x, the value of equation (2) is 1.

[0024] The second term probabilistically expresses the total number of occurrences of a reversal of the order of baggage x to be placed in the future. Specifically, it is the value obtained by multiplying the number of empty spaces where no baggage has been placed by the probability that a bag that will be taken out before baggage x will be brought in in the future. Here, if the number of empty spaces before baggage x is placed is s(x, l), and the cumulative probability that a bag that will be taken out in the opposite order to baggage x will occur in the future is p(x), then the second term of evaluation formula (1) can be expressed as the following formula (3).

[0025]

number

[0026] Figure 4 shows an example of the probability distribution of the arrival of a package with a certain delivery priority. The vertical axis of Figure 4 represents the probability of package arrival, and the horizontal axis represents the package's delivery priority. The smaller the delivery priority value, the higher the priority. For example, among delivery priorities 1 to 5, delivery priority 1 is the highest priority (more likely to be delivered early), and delivery priority 5 is the lowest priority. In other words, moving to the right in Figure 4 indicates a lower delivery priority (more likely to be delivered later). For example, if package x has a priority of a, the probability of a package appearing in the future that will reverse the delivery order of package x (a package with a lower delivery priority than package x) is shown in the shaded area in Figure 4. This shaded area is p(x) in equation (3). For example, if package x is placed in location 60-1, S(x, l) = 4, so in the calculation of row 50-1 for the delivered package x, the value of equation (3) is "4 × cumulative probability indicated by the shaded area in Figure 4."

[0027] The third term is a term that subtracts the amount included in the second term, which is the probability of an item being placed at that location in the past before placing package x on list l. The third term of evaluation formula (1) can be expressed as the following formula (4). In other words, in formula (3), S(x, l) = 4, but if the newly delivered package x is placed above x1 (for example, placement location 60-1), this is a process that subtracts the amount determined by placing package x in one of the four empty spaces. In other words, h3(x, l) represents the number of shufflings that will occur if package x is placed at placement location 60-1, which is included in the number of shufflings predicted by h2(x1, l) predicted before placing package x.

[0028]

number

[0029] Evaluation formula (1) is derived by subtracting the number of reversals when x' (leading) is placed from the number of reversals when x (following) is placed, with the aim of minimizing the increase in the number of reversals (number of times the goods are reordered) for two consecutively arriving goods x' (leading) and x (following). The detailed procedure is as follows:

[0030] For two pieces of luggage that arrive consecutively, we define an evaluation formula for the number of reversals (number of times luggage is reordered) when each piece is placed, and consider the difference between the evaluation value of the succeeding piece and the evaluation value of the preceding piece to be the increment in the number of reversals.The process of deriving this is shown below.

[0031] First, let F(x) be the evaluation value when a certain item x is brought in, f1(x, l) be the number of times the currently placed items will be reversed in each list at that time, and f2(x, l) be the number of times the items will be reversed in the future. This relationship can be expressed by the following equation (5).

[0032]

number

[0033] Here, if we define the preceding and succeeding pieces of luggage as x1 and x2, respectively, the increase is limited to the list l in which x2 is placed, and can be transformed into the following equation (6).

[0034]

number

[0035] Let us transform the first half of equation (6), "f1(x2, l)-f1(x1, l)". First, let us consider the load x a and x b The variable y takes the value 1 if is reversed and 0 otherwise. xa、xb Then, when a certain baggage x is placed, the baggage x placed on a certain list l is a The number of luggage that will be reversed, r(x, l, xa), is expressed as follows:

[0036]

number

[0037] Therefore, the first half of equation (6) can be transformed into the following equation (8).

[0038]

number

[0039] Next, we will transform the latter part of equation (6), "f2(x2, l) - f2(x1, l)." Here, let p(x) be the probability that the order of deliveries will be reversed with respect to future deliveries, and let S(x, l) be the number of deliveries that can be made on list l at the time that a certain package x arrives. In this case, the number of packages x' already placed that will be reversed with future deliveries at the time of arrival of a certain package x can be defined by the following equation (9).

[0040]

number

[0041] Next, using equation (9), we can transform the second half of equation (6) to obtain equation (10). The first term on the second line of equation (10) sums the number of inversions for each set of luggage XinList(x2, l) that is placed on list l when luggage x2 arrives. The second term calculates the value when luggage x2 arrives. The first term on the fourth line isolates only the number of inversions related to luggage x2. Finally, from lines 4 to 5, S(x2, l) - S(x1, l) decreases by the increase in luggage x2, so it becomes -1. This leads to the following equation (10).

[0042]

number

[0043] By substituting equations (8) and (10) into equation (2), the following equation (11) is derived.

[0044]

number

[0045] Finally, p(x) needs to be estimated lower than the normal probability distribution because it involves heuristics to avoid reversing the order of delivery. By introducing a parameter α to adjust this and transforming it into the following equation (12), we can derive evaluation equation (1).

[0046]

number

[0047] The planning system 10 calculates l that minimizes evaluation formula (1) for rows 50-1 to 5-5, and thereby plans the placement of cargo that will minimize the number of times cargo is handled no matter what cargo is brought in in the future. While Fig. 3 describes the case of calculating which row in a specific bay 40 cargo x should be placed in to reduce the number of times cargo is handled, it is possible to determine where in lane 30 cargo x should be placed by performing the same process for each bay 40 illustrated in Fig. 2A and selecting the row that best minimizes evaluation formula (1).

[0048] (operation) Next, the flow of the process for creating a package placement plan according to this embodiment will be described. FIG. 5 is a flowchart illustrating an example of a plan creation process according to the embodiment. First, the data acquisition unit 11 acquires data necessary for creating a plan, such as the layout of the lane 30, the cargo carry-out schedule, a probability distribution diagram of the cargo carry-out priority and occurrence probability shown in Fig. 4, the cargo already placed in the lane 30 and its location, the predicted value of the carry-out priority of each cargo, and test data for setting the parameter α (step S1). The data acquisition unit 11 writes and saves the acquired data in the storage unit 14.

[0049] Next, the parameter setting unit 121 calculates the value of the parameter α of the evaluation formula (1) (step S2). The test data includes, for example, a large amount of data on luggage that has already been placed in the lane 30 and luggage that will be carried in. For example, for luggage that has already been placed, the placement location and scheduled delivery date and time are defined. For luggage that will be carried in, the scheduled delivery date and time, delivery priority, and scheduled delivery date and time are defined. The parameter setting unit 121 performs a delivery simulation based on the scheduled delivery date and time defined for the luggage that will be carried in, which is included in the test data. In this case, the parameter setting unit 121 sets an arbitrary value between 0 and 1 for the parameter α, and performs the simulation using the evaluation formula definition unit 122 and the placement location determination unit 123. The evaluation formula definition unit 122 sets the value of the parameter α set by the parameter setting unit 121 to the evaluation formula (1). The placement location determination unit 123 searches for a row that minimizes evaluation formula (1) and places the item in an empty placement location (one of placement locations 60-1 to 60-5 in the example of FIG. 3) of that row. The parameter setting unit 121 performs a carry-in and placement simulation for the items to be carried in included in the test data. In parallel with this, the parameter setting unit 121 performs a carry-out simulation for the placed items and the items to be carried in included in the test data, according to the scheduled carry-out dates and times associated with each item. The parameter setting unit 121 prepares a variable for counting the number of times a carry-in occurs, and increments this counter by 1 each time a carry-in occurs during the carry-out simulation. The parameter setting unit 121 sets a parameter α to an arbitrary value between 0 and 1, executes a carry-in / carry-out simulation based on the test data, and counts the number of carry-ins that occurred during the simulation. When the simulation ends, the parameter setting unit 121 records the number of times that handling occurred during the simulation in association with the value of the set parameter α in the storage unit 14. Next, the parameter setting unit 121 changes the value of the parameter α and executes a carry-in / carry-out simulation using the same test data, counting and recording the number of times that handling occurred during the simulation. The parameter setting unit 121 changes the value of the parameter α and repeats the same process.For example, the parameter setting unit 121 may first set the parameter α to 0.1 and then execute a simulation, setting it to 0.2, and so on, changing the value of α in increments of 0.1 from 0.1 to 1.0 for a total of 10 simulations and counting the number of transfers. After completing multiple simulations, the parameter setting unit 121 selects the value of α that minimizes the number of transfers, records the selected value in the storage unit 14 as the best value of the parameter α, and outputs the selected value to the evaluation formula definition unit 122. Note that in a simulation performed by temporarily setting the value of α, multiple patterns of test data may be prepared, and a simulation may be performed using the test data for each pattern for one value of α, and the value with the smallest average number of transfers may be selected as the best value of the parameter α. Alternatively, α may be determined by selecting the value of the parameter α that most frequently results in a simulation result where the number of transfers is below a predetermined threshold, or by arbitrarily selecting from the α values ​​where the number of transfers is below a predetermined threshold.

[0050] Next, the evaluation formula definition unit 122 defines the evaluation formula (1) (step S3). The evaluation formula definition unit 122 sets the value of α selected by the parameter setting unit 121 in step S2 to the evaluation formula (1). This completes the preparation for the placement planning process.

[0051] Next, the data acquisition unit 11 acquires placement request data for the parcel to be carried in (step S4). The placement request data is data generated when a parcel to be placed somewhere in the lane 30 actually arrives. The placement request data includes the type of parcel and a predicted value of the carry-out priority. Next, the placement location determination unit 123 performs an optimization calculation to calculate which row (list) the parcel indicated by the placement request data should be placed in based on the evaluation formula (1) (step S5). The placement location determination unit 123 calculates the first term of the evaluation formula (1) based on the parcels already placed in each row 50, their predicted values ​​of their carry-out priorities, and the predicted value of the carry-out priority included in the placement request data. The placement location determination unit 123 calculates the second term of the evaluation formula (1) based on the number of vacant spaces in each row 50, the predicted value of the carry-out priority included in the placement request data, and a probability distribution diagram of the parcel's carry-out priority and occurrence probability. The placement location determination unit 123 calculates the third term of evaluation formula (1) based on the parcels already placed in each row 50, their predicted values ​​for removal priority, and a probability distribution diagram of the parcel removal priority and occurrence probability. The placement location determination unit 123 calculates the value of evaluation formula (1) using the first to third terms and the parameter α set in step S2, and searches for the row that minimizes this value. After calculating the row 50 that minimizes the value of evaluation formula (1), the placement location determination unit 123 determines the placement location 60 at the bottom of the empty space in the calculated row as the placement location of the parcel included in the placement request data. For example, if the value of evaluation formula (1) for row 50-1 is minimized, the placement location determination unit 123 determines placement location 60-1 as the placement location. Next, the output unit 13 outputs the placement locations (step S6). The output unit 13 displays the placement locations of the parcels included in the placement request data on a display device.

[0052] (effect) As described above, according to this embodiment, using probability distribution information indicating the relationship between the delivery priority of a package and the future occurrence probability of a package with such delivery priority, the difference between the evaluation value of the number of package reshuffles resulting from the delivery of a subsequent package, taking into account the number of package reshuffles resulting from a package to be delivered in the future, is calculated using evaluation formula (1). The package to be delivered is then determined to be placed at a location where this difference is smallest. This makes it possible to plan the placement of packages so that package reshuffles are minimized when the package is delivered, even when the order in which future packages are delivered is uncertain. This reduces the number of package reshuffles and the associated work time, thereby suppressing increases in fuel costs and work required to operate loading and unloading equipment.

[0053] In the above embodiment, an example of a cargo placement plan for a container terminal was given, but the present invention can also be applied to processes such as determining the placement location for cargo being brought in and out of a general logistics warehouse, in addition to container terminals.

[0054] FIG. 12 is a diagram illustrating an example of a hardware configuration of the planning system according to the embodiment. The computer 900 includes a CPU 901, a main memory device 902, an auxiliary memory device 903, an input / output interface 904, and a communication interface 905. The planning system 10 described above is implemented in the computer 900. The above-described functions are stored in the auxiliary memory device 903 in the form of a program. The CPU 901 reads the program from the auxiliary memory device 903, loads it into the main memory device 902, and executes the above-described processing in accordance with the program. The CPU 901 also allocates a storage area in the main memory device 902 in accordance with the program. The CPU 901 also allocates a storage area in the auxiliary memory device 903 for storing data being processed in accordance with the program.

[0055] A program for implementing all or part of the functions of the planning system 10 may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed to perform processing by each functional unit. The term "computer system" herein includes hardware such as an OS and peripheral devices. If a WWW system is used, the term "computer system" also includes the homepage provision environment (or display environment). The term "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, as well as storage devices such as hard disks built into the computer system. If the program is distributed to the computer 900 via a communication line, the computer 900 may load the program into the main storage device 902 and execute the above-described processing. The program may be for implementing part of the above-described functions, or may be capable of implementing the above-described functions in combination with a program already stored in the computer system.

[0056] As described above, several embodiments according to the present disclosure have been described, but all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as defined in the claims, as well as in the scope and spirit of the invention.

[0057] <Additional Notes> The planning system 10, the planning method, and the program described in each embodiment can be understood, for example, as follows.

[0058] (1) A planning system 10 according to a first aspect includes probability distribution information indicating the relationship between the priority of luggage to be removed and the probability of occurrence of the luggage; information on luggage already placed at a placement location and the scheduled removal of the luggage; an evaluation formula for calculating the difference between a first evaluation value calculated based on the probability distribution information for an evaluation value of the number of tasks of moving other luggage to remove the first luggage, which will be generated by placing a first luggage at the placement location, including luggage that will be brought in after the first luggage and placed at the placement location; and a second evaluation value calculated based on the probability distribution information for an evaluation value of the number of tasks that will be generated by placing a second luggage at the placement location, which will be brought in after the second luggage, including luggage that will be brought in after the second luggage; and a placement location determination unit that calculates the placement location of the second luggage based on the evaluation formula. This makes it possible to create a cargo placement plan that reduces the number of times cargo is rearranged, even when the cargo delivery schedule is uncertain.

[0059] (2) The planning system 10 according to the second aspect is the planning system of (1), wherein the evaluation formula includes a first term that calculates an evaluation value of the number of tasks that will occur between the second luggage and the other luggage that has already been placed by placing the second luggage, and a second term that calculates an evaluation value of the number of tasks that will occur between the second luggage and the luggage that will be brought in and placed after the second luggage has been placed. By calculating evaluation values ​​for cargo that will be delivered in the future, it is possible to create a cargo placement plan that reduces the number of times cargo is rearranged, even if the cargo delivery schedule is not yet confirmed.

[0060] (3) The planning system 10 according to a third aspect is the planning system of (2), in which the second term in the evaluation formula is multiplied by a weighting coefficient. For terms relating to the future, the weighting coefficient is used to adjust the degree to which future assumptions conform to probability, thereby maintaining the predictive accuracy of the evaluation formula.

[0061] (4) The planning system 10 according to the fourth aspect is the planning system of (3), and further includes a parameter setting unit that simulates the loading, placement, and unloading of cargo while changing the value of the weighting coefficient, records the number of times the work occurs during the simulation, and calculates the value of the weighting coefficient when the number of times the work occurs is equal to or less than a threshold value. This allows the weighting coefficient values ​​to be set appropriately.

[0062] (5) The planning system 10 according to the fifth aspect is a planning system of (1) to (4), in which h1(x, l) represents the number of operations between the already placed luggage when luggage x is placed at the row placement location l, h2(x, l) represents the number of operations between luggage to be delivered in the future and luggage x, h3(x, l) represents the number of operations when luggage x is placed that is included in the number of operations predicted before luggage x is placed, and α is a weighting coefficient, the evaluation formula is h1(x, l) + α(h2(x, l) - h3(x, l)). This makes it possible to create a cargo placement plan that reduces the number of times cargo is rearranged, even when the cargo delivery schedule is uncertain.

[0063] (6) A planning method according to a sixth aspect calculates the placement location of a second piece of luggage based on information on luggage already placed at a placement location and the scheduled removal of the luggage, and an evaluation formula for calculating the difference between a first evaluation value calculated based on probability distribution information showing the relationship between the removal priority of the luggage and the occurrence probability of the luggage, for the evaluation value of the work of moving other luggage to remove the first piece of luggage that occurs when the first piece of luggage is placed at the placement location, including luggage that will be brought in after the first piece of luggage and placed at the placement location, and a second evaluation value calculated based on the probability distribution information, for the evaluation value of the work that occurs when a second piece of luggage that will be brought in after the first piece of luggage is placed at the placement location, including luggage that will be brought in after the second piece of luggage and placed at the placement location.

[0064] (7) A program according to a seventh aspect causes a computer 900 to execute a process of calculating a placement location for a second piece of luggage based on information on luggage already placed at a placement location and the scheduled removal of the luggage, and an evaluation formula for calculating the difference between a first evaluation value calculated based on probability distribution information showing the relationship between the removal priority of the luggage and the occurrence probability of the luggage, for the work of moving other luggage to remove the first piece of luggage that occurs when the first piece of luggage is placed at the placement location, including luggage that will be brought in after the first piece of luggage and placed at the placement location, and a second evaluation value calculated based on the probability distribution information, for the work that occurs when a second piece of luggage that will be brought in after the first piece of luggage is placed at the placement location, including luggage that will be brought in after the second piece of luggage and placed at the placement location. [Explanation of symbols]

[0065] 10. Planning System 11. Data acquisition section 12. Planning Department 121 Parameter setting section 122...Evaluation expression definition section 123... Placement location determination unit 13. Output section 14...Storage section 900···Computer 901 CPU 902...Main memory 903...Auxiliary storage device 904 Input / Output Interface 905···Communication Interface

Claims

1. Probability distribution information indicating the relationship between the priority of carrying out a package and the probability of occurrence of the package; Information on the luggage already placed at the placement location and the planned removal of the luggage; an evaluation formula for calculating the difference between a first evaluation value calculated based on the probability distribution information for an evaluation value of the number of operations to move other luggage in order to remove the first luggage, which occurs when a first luggage is placed at the placement location, and which includes luggage that is brought in after the first luggage and placed at the placement location; and a second evaluation value calculated based on the probability distribution information for an evaluation value of the number of operations to be caused when a second luggage is placed at the placement location, which is to be brought in after the second luggage, and which includes luggage that is brought in after the second luggage and placed at the placement location; a placement location determination unit that calculates a placement location of the second package based on the evaluation formula; A planning system that includes:

2. The evaluation formula includes a first term for calculating an evaluation value of the number of operations that will occur between the second item and the other item that has already been placed by placing the second item, and a second term for calculating an evaluation value of the number of operations that will occur between the second item and an item that will be brought in and placed after the second item has been placed. The planning system of claim 1 .

3. The second term in the evaluation formula is multiplied by a weighting coefficient. The planning system of claim 2 .

4. a parameter setting unit that simulates placement and removal of luggage while changing the value of the weighting coefficient, records the number of times the work occurs during the simulation, and calculates the value of the weighting coefficient when the number of times the work occurs is equal to or less than a threshold value; The planning system of claim 3 further comprising:

5. Let h1(x, l) represent the number of operations between luggage x and the already placed luggage when the luggage x is placed at the row placement location l, let h2(x, l) represent the number of operations between luggage to be delivered in the future and luggage x, let h3(x, l) represent the number of operations when luggage x is placed that is included in the number of operations predicted before the placement of luggage x, and let α be a weighting coefficient, then the evaluation formula is h1(x, l) + α(h2(x, l) - h3(x, l)). The planning system of claim 1 .

6. Information on the luggage already placed at the placement location and the planned removal of the luggage; an evaluation formula for calculating the difference between a first evaluation value calculated based on probability distribution information indicating the relationship between the delivery priority of a first piece of luggage and the occurrence probability of the piece of luggage, for moving other pieces of luggage to remove the first piece of luggage, and a second evaluation value calculated based on the probability distribution information, for the evaluation value of the work caused by the placement of a second piece of luggage to the placement location, for moving other pieces of luggage to remove the first piece of luggage, and a second evaluation value calculated based on the probability distribution information, for the evaluation value of the work caused by the placement of a second piece of luggage to the placement location, for moving other pieces of luggage to remove the first piece of luggage, and and calculating a location of the second package based on the calculated location. Planning methods.

7. On the computer, Information on the luggage already placed at the placement location and the planned removal of the luggage; an evaluation formula for calculating the difference between a first evaluation value calculated based on probability distribution information indicating the relationship between the delivery priority of a first piece of luggage and the occurrence probability of the piece of luggage, for moving other pieces of luggage to remove the first piece of luggage, and a second evaluation value calculated based on the probability distribution information, for the evaluation value of the work caused by the placement of a second piece of luggage to the placement location, for moving other pieces of luggage to remove the first piece of luggage, and a second evaluation value calculated based on the probability distribution information, for the evaluation value of the work caused by the placement of a second piece of luggage to the placement location, for moving other pieces of luggage to remove the first piece of luggage, and and a program for executing a process of calculating a placement location of the second package based on the above.

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