JP4492844B2 - Data processing device - Google Patents

Description

  The present invention relates to a data processing apparatus that generates data of a collection plan for collecting a plurality of types of conveyance targets that are distributed and stocked at a plurality of inventory locations to a collection position by at least one target conveyance means that is movable.

  Currently, imported products and other items to be transported may be distributed in stock at multiple locations in the warehouse, and when they are unloaded, they are picked up by a target transport means such as a forklift to the specified collection position. To do.

  Since the above-described collection is performed by a forklift operator by intuition, an optimal collection operation may not be performed. In particular, when the worker is not familiar with the collection work, the collection work is often inefficient.

  In addition, since the applicant does not develop a data processing apparatus for generating a collection plan data as a normal business and has no experience in patent applications, the applicant has not been able to detect a publicly known example corresponding to the present plan.

  The present invention has been made in view of the above-described problems, and efficiently transports a plurality of types of transport targets distributed and stocked at a plurality of stock locations to a pickup position by at least one target transport means that is movable. An object of the present invention is to provide a data processing apparatus capable of generating data for a collection plan to be collected.

  The first data processing apparatus according to the present invention generates data for a collection plan for collecting a plurality of types of conveyance objects distributed in a plurality of inventory locations to a predetermined collection position by at least one movable object conveyance means. The data processing apparatus includes a map storage unit, an inventory storage unit, a condition storage unit, a target input unit, an inventory detection unit, a route search unit, and a route output unit.

  The map storage means stores a route chart composed of travel routes in which the transport time of the transport target by the target transport means is converted to the travel distance, and the stock storage means is the transport target stocked for each stock location. Is stored. The condition storage means stores data on the quantity of the transport target that can be transported by the target transport means at one time, and the target input means receives the data input of the type and quantity of the transport target to be collected at the collection position. The inventory detection means detects a plurality of inventory locations in which the data input transport targets are in stock from the stored data of the inventory storage means, and the route search means detects the plurality of data input transport targets. A data collection plan for collecting goods at a shortest distance in the route chart from a plurality of inventory locations to a pickup position is searched for data by the SA method with reference to data stored in the condition storage means. Since the route output means outputs the collection plan searched for data, the data processing apparatus of the present invention collects the conveyance object at the shortest distance when the type and quantity of the conveyance object to be collected are input. The collection plan is output as a collection plan.

  The second data processing apparatus of the present invention has a map input means and a chart generation means, and the map input means includes a plurality of inventory locations in which a plurality of types of transport targets are distributed and a movable target. The physical arrangement with the collection position where the conveyance object is collected is input by the conveyance means. Since the chart generation means generates the data of the route chart including the movement path in which the transport time of the transport target by the target transport means is converted into the travel distance from the physical arrangement inputted as data, the data processing apparatus of the present invention When the physical arrangement of the location and the pickup position is input as data, a route chart including a movement route in which the conveyance time of the conveyance target by the target conveyance means is converted into the movement distance is generated.

  The automatic transfer warehouse of the present invention is an automatic transfer warehouse having a plurality of inventory locations where a plurality of types of transfer targets are distributed and stocked and one pickup position, and includes at least one target transfer means, a map Storage means, inventory storage means, condition storage means, target input means, inventory detection means, route search means, and equipment control means.

  The target transport means is movable and collects the transport target from the inventory location to the collection position, and the map storage means stores a route chart consisting of a travel route in which the transport time of the transport target by the target transport means is converted into a travel distance. I remember it. The stock storage means stores data on the transport targets stocked for each stock location, and the condition storage means stores data on the quantity of transport targets that can be transported at one time by the target transport means. The object input means inputs the type and quantity of the conveyance target to be collected at the collection position, and the inventory detection means extracts a plurality of inventory locations where the data input conveyance objects are in stock from the storage data of the inventory storage means. Detect data. The route search means uses the SA method to collect a collection plan for collecting a plurality of transport targets to which data has been input from a plurality of detected inventory locations to a collection position at the shortest distance in the route chart with reference to the data stored in the condition storage means. The data search is performed, and the equipment control unit causes the target transfer unit to collect the transfer target from the inventory location to the pickup position in the data-searched collection plan. Therefore, when the type and quantity of the transport target to be collected are inputted as data, the automatic transport warehouse of the present invention collects the transport target at the pick-up position at the shortest distance by the target transport means.

  The various means referred to in the present invention need only be formed so as to realize the function. For example, dedicated hardware that exhibits a predetermined function, a data processing apparatus provided with a predetermined function by a computer program It can be realized as a predetermined function implemented in the data processing apparatus by a computer program, a combination thereof, or the like.

  In addition, the various constituent elements referred to in the present invention do not have to be independent of each other, a plurality of constituent elements are formed as one member, and a constituent element is a part of another constituent element. It is also possible that a part of a certain component and a part of another component overlap.

  Further, the information storage medium referred to in the present invention may be hardware in which a computer program for causing the data processing apparatus to execute various processes is stored in advance, for example, a ROM ( It can be implemented with Read Only Memory (HDD), Hard Disk Drive (HDD), CD (Compact Disc) -ROM or FD (Flexible Disc-cartridge), or a combination of these, which can be loaded in a data processing device. is there.

  In addition, the data processing apparatus referred to in the present invention may be hardware that can read a computer program and execute a corresponding processing operation. For example, a CPU (Central Processing Unit) is mainly used, and a ROM, a RAM ( Random Access Memory), I / F (Interface) units, and other hardware connected to various devices may be used.

  In the present invention, causing the data processing apparatus to execute various operations corresponding to the computer program also means causing the data processing apparatus to control operations of the various devices. For example, storing various data in the data processing device means that the CPU stores various data in an information storage medium such as a RAM fixed to the data processing device, and an FD that is exchangeably loaded in the data processing device. The CPU may store various data in an information storage medium such as FDD (FD Drive).

  In the first data processing apparatus according to the present invention, when the type and quantity of the transport target to be collected are input as data, a collection plan for collecting the transport target at the shortest distance is searched for data by the SA method, and the data is output. For example, it is possible to efficiently collect a plurality of conveyance objects at the shortest distance by the object conveyance means corresponding to the collection plan output as data.

  In the second data processing apparatus of the present invention, when the physical arrangement of the inventory location and the pickup position is input as data, a route chart including a movement route in which the conveyance time of the conveyance target by the target conveyance means is converted into a movement distance. Therefore, it is possible to generate a route chart effective for data generation of a collection plan.

  In the automatic transport warehouse of the present invention, when the type and quantity of the transport target to be picked up are input, data search is performed for the pick-up plan for picking up the transport target at the shortest distance by the SA method, and corresponding to the pick-up plan. A plurality of conveyance objects can be efficiently collected at the collection position at the shortest distance by the object conveyance means.

[Configuration of the embodiment]
An embodiment of the present invention will be described below with reference to the drawings. The data processing apparatus 100 according to the present embodiment is installed in, for example, a temporary inventory warehouse 200 (not shown) that temporarily stocks various types of transportation targets, and the data of the collection plan of the transportation targets in the temporary inventory warehouse 200. Used for generation.

  More specifically, as shown in FIG. 4, the temporary inventory warehouse 200 exemplified in this embodiment includes a plurality of flat racks 201 and a plurality of electric racks 202 arranged at predetermined positions as stock locations. A plurality of types of transport objects (not shown) such as petroleum product pail cans are distributed and stocked in the flat / electric racks 201 and 202.

  There is a single collection position 203 at a predetermined position away from the flat / electric racks 201 and 202, and various transport targets are placed in a plurality of flat positions by a forklift (not shown) which is a movable target transport means. Pickup is performed from the mounting / electric racks 201 and 202 to one pickup position 203. Note that the movement path 204 on which the forklift can actually move is defined in advance, and the distance of the movement path 204 is also measured.

  The flat rack 201 has a flat upper surface, and various transport objects are simply placed on the upper surface (not shown). For this reason, a specific unloading time is not required for the unloading work to be transported by the forklift, and a plurality of forklifts can simultaneously execute unloading work for one flat rack 201.

  The electric rack 202 is composed of a plurality of shelf-shaped storage racks that are electrically moved, and various conveyance objects are three-dimensionally stored in the storage rack (not shown). For this reason, when the forklift unloads the transfer target from the electric rack 202, the storage rack is moved so that the target transfer target is exposed, enters the gap between the storage racks generated by the movement, and the transfer target is unloaded. .

  Therefore, in the electric rack 202, the forklift requires a specific carrying-out time for carrying-out work, and a plurality of forklifts cannot simultaneously carry out the carrying-out work for one electric rack 202.

  In this embodiment, a plurality of forklifts such as five are arranged in the temporary inventory warehouse 200, and these forklifts normally stand by at the pickup position 203. For example, the data processing apparatus 100 of this embodiment is also arranged at the collection position 203, and generates a collection plan notified to a forklift operator.

  As shown in FIG. 3, the data processing apparatus 100 according to the present embodiment includes a CPU 101 as hardware serving as a computer main body. A ROM 103, a RAM 104, an HDD 105, and an FD 106 are exchanged for the CPU 101 through a bus line 102. Hardware such as an FDD 107 that can be freely loaded, a CD drive 109 on which a CD-ROM 108 can be freely loaded, a keyboard 110, a mouse 111, a display 112, and an I / F unit 113 are connected.

  In the data processing apparatus 100 of this embodiment, hardware such as the ROM 103, RAM 104, HDD 105, exchangeable FD 106, exchangeable CD-ROM 108, etc. corresponds to an information storage medium, and at least one of them is a computer program for the CPU 101. And resources are stored as software.

  Such software is installed in the data processing apparatus 100 in advance, and is read by the CPU 101 when the data processing apparatus 100 is activated. As described above, when the CPU 101 reads an appropriate computer program and executes various processes, the data processing apparatus 100 according to the present embodiment has a map input unit 301, a chart generation unit 302, a map registration, as shown in FIG. Means 303, route detection means 304, shortest registration means 305, map storage means 311, inventory storage means 312, condition storage means 313, shortest storage means 314, target input means 316, inventory detection means 317, route search means 318, route output Various means such as means 319 are logically provided as various functions.

  Further, as shown in FIG. 2, the route search means 318 includes an initial generation means 321, a random change means 322, an evaluation calculation means 323, a difference calculation means 324, a first replacement means 326, a second replacement means 327, and an operation control means. 328, a variable update unit 329, a process control unit 331, a result determination unit 332, and the like. The random change unit 322 includes a 2-opt neighborhood unit 334 and a random neighborhood unit 335.

  The various input means 301 and 316 correspond to the function of the CPU 101 recognizing the input data of the keyboard 110 and the I / F unit 113 corresponding to the computer program stored in the RAM 104, and the path output means 319 is a computer program. The CPU 101 corresponds to the function of causing the display 112 to display data.

  The various storage units 311, 312,... Correspond to storage areas constructed in the HDD 105 so that the CPU 101 can recognize them, and the various registration units 303, 305 have functions for the CPU 101 to perform data registration in the storage area of the HDD 105. The other various means 302, 304,... Correspond to functions for the CPU 101 to execute predetermined data processing.

  As shown in FIG. 4, the map input means 301 receives the physical arrangement of a plurality of flat / electric racks 201 and 202 and one pickup position 203 together with various attribute data, and the chart generation means 302 As shown in FIG. 5, the route diagram 210 is generated from the physical layout that has been input.

  More specifically, as described above, the flat rack 201 does not require a specific unloading time for unloading work by a forklift and can perform unloading work simultaneously by a plurality of forklifts. It takes time and can't carry out unloading work with multiple forklifts at the same time.

  Therefore, when the physical arrangement of the plurality of flat / electric racks 201 and 202 is input to the data processing apparatus 100 as described above, a specific carry-out time is also input for each of the electric racks 202. Whether data can be simultaneously operated or not is also input for each flat / electric rack 201, 202.

  In the route chart 210 generated from these input data, the moving route 204 is composed of a large number of arcs 212 in a predetermined unit appropriately connected via a node 211, and the flat / electric racks 201 and 202, the pickup position 203, and the like. Consists of a part of a large number of nodes 211, and each of the large number of nodes 211 is individually assigned an identification number.

  In other words, the physical arrangement of the flat / electric racks 201 and 202 and the pickup position 203 is converted into the node 211, and the movement path connecting the nodes 211 of the flat / electric racks 201 and 202 and the pickup position 203 is connected. 204 is converted into a large number of arcs 212 sequentially connected via a large number of nodes 211.

  At this time, for example, as shown in FIG. 4, the moving path 204 through which the forklift can access one electric rack 202 “G” is “24 (m)”, and the unit of the arc 212 is “4.0 (m). ””, The one electric rack 202 is converted into six nodes 211 “G-1” to “G-6” as shown in FIG.

  Furthermore, since the unloading time of the electric rack 202 is converted into a movement distance, the arc 212 connected to the node 211 of the electric rack 202 is increased in accordance with the converted movement distance. In addition, as described above, the data indicating that the simultaneous work cannot be performed is input to the electric rack 202, and therefore, the arc 212 connected only to the node 211 of the electric rack 202 is given data as the attribute.

  In the actual temporary inventory warehouse 200, as shown in FIG. 4, the flat / electric racks 201 and 202, the pickup position 203, and the like are normally arranged in a rectangular range, but in the data processing apparatus 100 of this embodiment, The arc 212 connected to the electric rack 202 is increased as described above.

  For this reason, the node 211 and the like of the electric rack 202 project greatly outward as they are, but the diagram generating means 302 bends the linear movement path 204 projecting outward to make the path diagram 210 of the display 112. Molding into a predetermined rectangular range corresponding to the display screen.

  Since the map registration unit 303 registers the route diagram 210 generated by the diagram generation unit 302 in the map storage unit 311, the map storage unit 311 stores the route diagram 210 registered as data.

  The route detection unit 304 is the shortest distance travel route 204 for each combination of a plurality of flat / electric racks 201 and 202 and one pickup position 203 from the route diagram 210 generated by the diagram generation unit 302. The shortest path is detected by the Dijkstra method.

  The shortest registration unit 305 registers the shortest path detected by the path detection unit 304 in the shortest storage unit 314. Therefore, the shortest storage unit 314 includes a plurality of flat / electric racks 201 and 202 and one pickup. The shortest path is stored as data for each combination with the position 203.

  The stock storage means 312 stores data on the objects to be transported stocked for each of the flat / electric racks 201 and 202, and the condition storage means 313 includes the number of forklifts used at one time in the temporary stock warehouse 200, The number of conveyance targets that the forklift can convey at one time is stored as a constraint condition.

  The storage data of the stock storage means 312 is constantly updated by manual input operation or the like corresponding to the stock status of the temporary inventory warehouse 200, and the storage data of the condition storage means 313 is the forklift in the temporary inventory warehouse 200. Input operation is performed in advance according to the operation status. In this embodiment, the performance of a plurality of forklifts is uniform for the sake of simplicity.

  The object input means 316 receives the data of the type and quantity of the conveyance target to be collected at the collection position 203, and the inventory detection means 317 includes a plurality of flat / electric racks 201, in which the data input conveyance objects are in stock. 202 is detected from the data stored in the inventory storage means 312.

  More specifically, when a data processing device 100 in a predetermined input state is input and operated by a manual operation of the keyboard 110 or the like, the data processing device 100 receives the CPU 101. By using the input data as a search key, data is detected from a plurality of flat / electric racks 201 and 202 stocked for conveyance from a predetermined data file in the HDD 105.

  The route search means 318 includes a map storage means 311 and a condition storage means for collecting a collection plan for collecting a plurality of transport targets to which data is input from a plurality of flat / electric racks 201 and 202 whose data has been detected to a collection position 203 in the shortest time. Data search is performed by the SA method with reference to the data stored in 313 and the shortest storage unit 314, and the route output unit 319 outputs the data collection plan searched for data by the display output of the display 112 or the like.

  As described above, when the route search unit 318 searches for data in the collection plan, the initial generation unit 321 is one of the collection plans for collecting a plurality of conveyance targets from the plurality of flat / electric racks 201 and 202 to the collection position 203. The next solution is generated as data, and the random changing means 322 randomly changes the movement path 204 of the first solution to generate a second solution.

  More specifically, when the types and quantities of a plurality of transport targets to be collected are input together with a plurality of flat / electric racks 201 and 202 in which the transport targets are stocked, the initial generation means 321 is so-called. Based on the algorithm for solving the traveling salesman problem, a primary solution of a collection plan for collecting a plurality of objects to be transported from the collection position 203 to the collection position 203 through a plurality of flat / electric racks 201 and 202 is generated as data.

  At that time, the initial generation unit 321 stores a plurality of transport targets to be collected corresponding to the number of transport targets that can be transported by the forklift and the number of forklifts that can be used at a time, which are stored in the data in the condition storage unit 313. Data is searched for a collection plan based on the shortest route stored in the route search means 318 simply by sequentially assigning to a plurality of forklifts.

  Further, in the route chart 210 stored as data in the map storage means 311, since the arc 212 of the moving route 204 connected only to the node 211 of the electric rack 202 is given data indicating that simultaneous work is impossible, the initial value is given. The generation unit 321 generates data of the primary solution of the collection plan so that a plurality of forklifts are not simultaneously positioned on the arc 212 described above.

  In that case, when the data for the movements of the plurality of forklifts on the movement paths 204 that cannot be simultaneously performed are detected, the initial generation unit 321 assigns the order of movement of the movement paths 204 to the plurality of forklifts that have been detected by the FIFO rule.

  At this time, as shown in FIG. 6, the waiting time is set for the next forklift until the previous forklift is separated from the simultaneous impossible movement path 204, and the movement of a plurality of forklifts along the simultaneous impossible movement path 204 is performed. Time division.

  The random changing means 322 generates a secondary solution by combining the 2-opt neighborhood of the primary solution collection plan by the 2-opt neighborhood means 334 and the random neighborhood of the primary solution collection plan by the random neighborhood means 335. To do.

  More specifically, when the forklift travels around the plurality of flat / electric racks 201 and 202 to the collection position 203 in the primary solution collection plan, the 2-opt proximity means 334 A secondary solution is generated by randomly exchanging a plurality of flat / electric racks 201 and 202 of the next solution.

  For example, as illustrated in FIG. 7, when a transport target is collected from a node 211 having a collection position 203 of “18” and a node 211 of “3, 4, 8”, as illustrated in FIG. When the node 211 “4, 8” of the primary solution “→ 4 → 8 → 3 → 18” is exchanged, “18 → 8 → 4 → 3 → 18” is obtained as shown in FIG. 7B. A quadratic solution is generated.

  In addition, when there are a plurality of pickup operations in which the forklift moves from the pickup position 203 to the pickup position 203 via the flat / electric racks 201 and 202 in the primary solution pickup plan, the random neighborhood means 335 A secondary solution is generated by randomly exchanging the flat / electric racks 201 and 202 having the same quantity to be conveyed in a plurality of pickup operations.

  Further, in the present embodiment, since a plurality of forklifts are used at a time as described above, the random proximity means 335 also randomly arranges the flat / electric racks 201 and 202 having the same number of objects to be transported in the pickup operation of the plurality of forklifts. Replace with. The random proximity means 335 also randomly changes the number of forklifts used at one time, and randomly changes the allocation of the plurality of flat / electric racks 201 and 202 to the plurality of forklifts.

  For example, as shown in FIG. 8, when a transport target is picked up by two forklifts from a node 211 whose collection position 203 is “18” and “3, 4, 8, 11”, FIG. As shown in FIG. 4, when some nodes 211 of the primary solution “18 → 11 → 18” “18 → 8 → 4 → 3 → 18” are exchanged, “18 → 11 → 8 → 18” “18” A quadratic solution of 4 → 3 → 18 ”is generated as data.

  The evaluation calculation means 323 calculates the required time of the primary solution, the secondary solution, and the collection plan as evaluation values, respectively, and the difference calculation means 324 calculates the difference obtained by subtracting the evaluation value of the primary solution from the evaluation value of the secondary solution. The value ΔI is calculated. More specifically, the evaluation calculation unit 323 converts the movement distance of the collection plans of the plurality of forklifts into the movement time, and calculates the total time obtained by adding the waiting time to the movement time as the evaluation value.

  For example, as shown in FIGS. 7A and 7B, a secondary solution “18 → 8 → 4 → 3 → 18” is generated from a primary solution “18 → 4 → 8 → 3 → 18”. Then, since the number of arcs 212 corresponding to the required time is reduced from “16” to “14”, the difference value ΔI becomes “−2”.

  The first replacement means 326 replaces the primary solution with the secondary solution if the difference value ΔI is a negative value, and the second replacement means 327 determines that “d <exp (Δ) even if the difference value ΔI is not a negative value. If I / T) (d is a uniform random number of “0 ≦ d <1” and T is a predetermined variable) ”, the primary solution is replaced with the secondary solution.

  The operation control means 328 repeats the processing operations of the random change means 322, the evaluation calculation means 323, the difference calculation means 324, the first replacement means 326, and the second replacement means 327 up to a predetermined number of times, and the variable update means 329 When the operation is repeated a predetermined number of times, the variable T is updated with data by multiplication by a predetermined constant γ of “1” or less.

  The processing control unit 331 repeats the processing operation of the operation control unit 328 every time the variable T is updated, and the result determination unit 332 performs the secondary solution even if the processing operation of the operation control unit 328 is repeated a predetermined number of times. The primary solution that is not replaced with is determined as the collection plan, and the primary solution is also determined as the collection plan when the processing operation of the processing control means 331 is repeated a predetermined number of times.

  Various means of the data processing apparatus 100 as described above are realized by using hardware such as the HDD 105 and the I / F unit 113 as necessary. The main unit is a computer program stored in an information storage medium such as the RAM 104. This is realized by the function of the CPU 101 which is hardware corresponding to the above.

  Such a computer program, for example, inputs data by the keyboard 110, the I / F unit 113, etc. of the physical arrangement of various flat / electric racks 201, 202 and one pickup position 203 and various attribute data. Accepting, generating data of a route diagram 210 composed of a large number of nodes 211 and arcs 212 corresponding to the physical arrangement and attribute data inputted as data, and storing the generated route diagram 210 as a data file in the HDD 105 or the like Data registration, data detection using the Dijkstra method for detecting the shortest path for each combination of a plurality of flat / electric racks 201, 202 and one pickup position 203 from the generated route chart 210. Data registration of the shortest path, flat / electric rack 201, 20 The storage targets stored for each time are stored as data, and the number of forklifts used at one time in the temporary inventory warehouse 200 and the number of transfer targets that the forklift can transport at a time are stored as constraints. Receiving the data input of the type and quantity of the transport target to be picked up at the pick-up position 203, and storing the plurality of flat / electric racks 201, 202 in which the transport target that has been data-stored is stocked from the stored data. Detecting and collecting a plurality of objects to be transported from a plurality of flat / electric racks 201 and 202 from which data is detected to a collection position 203 in the shortest time with reference to various stored data, the SA method To search for data, and to output the data collection plan searched for on the display 112 The processing operation etc. is stored in the information storage medium RAM104 such as software to be executed by the CPU101 and the like.

  Further, the computer program for searching the data for the above-mentioned collection plan by the SA method is to obtain a primary solution of the collection plan for collecting a plurality of transport targets from a plurality of flat / electric racks 201 and 202 to a collection position 203 by a plurality of forklifts. When the forklift travels around the plurality of flat / electric racks 201, 202 from the collection position 203 to the collection position 203 in the primary solution collection plan, the plurality of flat / electric racks 201 , 202 are randomly exchanged to generate secondary solution data, and in the primary solution collection plan, the forklift moves from the collection position 203 to the collection position 203 via the flat / electric racks 201, 202. When there are a plurality, the flat / electric racks 201 and 202 having the same quantity to be transported in a plurality of pickup operations are randomly exchanged. Generating data for the next solution, randomly exchanging the flat / electric racks 201 and 202 having the same quantity to be transported in the pickup operation of a plurality of forklifts when generating the data for the second solution, The number of forklifts used at one time when generating data is also randomly changed, and the allocation of a plurality of flat / electric racks 201 and 202 to a plurality of forklifts is also randomly generated when generating a secondary solution. Changing, calculating the required time of the primary solution, the secondary solution and the collection plan as evaluation values, respectively, and calculating the difference value ΔI obtained by subtracting the evaluation value of the primary solution from the evaluation value of the secondary solution If the difference value ΔI is a negative value, the primary solution is replaced with a secondary solution. If the difference value ΔI is not a negative value, “d <exp (ΔI / T)” is satisfied. Is replaced with a quadratic solution, the above-mentioned quadratic solution The processing operation from solution generation to replacement is repeated up to a predetermined number of times, and when the processing operation is repeated up to the predetermined number of times, the variable T is updated with data by a predetermined constant γ of “1” or less, and the variable T is updated with data. Each time it is done, the processing operation from the data generation of the secondary solution described above to the data update of the variable T is repeated, and the primary solution that is not replaced by the secondary solution even if this processing operation is repeated a predetermined number of times as a collection plan It is stored in an information storage medium such as the RAM 104 as software for causing the CPU 101 or the like to execute processing operations such as determining, confirming the primary solution as a collection plan even when the processing operation is repeated a predetermined number of times. Yes.

[Operation of the embodiment]
In the configuration as described above, a data processing method by the data processing apparatus 100 of the present embodiment will be described below. For example, first, when the data processing apparatus 100 is used in a certain temporary inventory warehouse 200, as shown in FIG. 4, a plurality of flat / electric racks 201 and 202 of the temporary inventory warehouse 200 and one pickup position 203 The operator inputs data to the data processing apparatus 100 by manual operation of the keyboard 110 together with various attribute data such as the unloading time for each electric rack 202 and the inability to perform simultaneous work on the electric rack 202.

  Then, in this data processing device 100, as shown in FIG. 9, the route diagram 210 is generated by a predetermined algorithm from various data of the temporary inventory warehouse 200 inputted as data (step S1), The route chart 210 stores data in the HDD 105 or the like (step S3).

  When the route diagram 210 is generated in this way, as shown in FIG. 5, the moving route 204 is converted into data of a large number of arcs 212 of a predetermined unit appropriately connected via the node 211, and the flat / electric rack 201 and 202 and the pickup position 203 are generated as a part of many nodes 211.

  Further, the carry-out time of the electric rack 202 described above is converted into a moving distance, and the arc 212 connected to the node 211 of the electric rack 202 is increased, and the arc 212 connected only to the node 211 of the electric rack 202 is simultaneously added. Inability to work is given as an attribute. Further, the linear movement path 204 protruding outward is bent, and the outer shape of the path chart 210 is formed into a predetermined rectangular range corresponding to the display screen of the display 112.

  Next, the shortest path, which is the shortest distance travel path 204 for each combination of a plurality of flat / electric racks 201 and 202 and one pickup position 203, is obtained by the Dijkstra method. Data is detected (step S4), and the shortest distance is registered in the HDD 105 or the like (step S5).

  Further, the worker determines the transport target stocked for each flat / electric rack 201, 202, the number of forklifts used at one time in the temporary inventory warehouse 200, the number of transport targets that the forklift can transport at one time, and the like. When data is input to the data processing apparatus 100 by manual operation of the keyboard 110, the input data is also registered in the HDD 105 or the like.

  When the various data registrations as described above are completed, the data processing apparatus 100 is ready to output the collection plan in response to the data input of the collection request. Therefore, when a request to collect the conveyance target at the collection position 203 is generated, the operator inputs the type and quantity of the conveyance target to the data processing apparatus 100 by manual operation of the keyboard 110, as shown in FIG. (Step T1).

  Then, in this data processing apparatus 100, the plurality of flat / electric racks 201 and 202 in which the data input transport targets are in stock are detected from the storage data such as the HDD 105 (step T2), and the plurality of data input are input. A data collection plan is collected by the SA method in the shortest time from the plurality of flat / electric racks 201, 202 whose data is detected to the collection position 203 (step T3).

  More specifically, as shown in FIG. 11, in the data processing apparatus 100, first, a primary solution of a collection plan for collecting a plurality of conveyance targets from a plurality of flat / electric racks 201 and 202 to a collection position 203 is Data is generated by a solution algorithm for the so-called traveling salesman problem (step E2).

  In that case, a plurality of transport targets to be collected corresponding to the number of transport targets that can be transported by the forklift and the number of forklifts that can be used at one time are simply assigned to the multiple forklifts in order, and the shortest registered data. Based on the route, the primary solution of the pickup plan is searched for data.

  When the primary solution is generated in this way, the simultaneous failure is given to the arc 212 of the moving path 204 connected only to the node 211 of the electric rack 202. When the movement of the plurality of forklifts is detected, as shown in FIG. 6, the order in which the movement path 204 is moved is given to the plurality of forklifts detected by the data according to the FIFO rule. The waiting time is set for the next forklift until the forklift is released.

  When the primary solution of the collection plan is generated as described above, the secondary solution is generated from the primary solution by the vicinity of the 2 opt and the random vicinity (step E3). More specifically, when the forklift moves around the plurality of flat / electric racks 201 and 202 to the collection position 203 from the collection position 203 in the collection plan of the primary solution, the plurality of flat placement / The electric racks 201 and 202 are exchanged at random, and a secondary solution is generated.

  For example, as illustrated in FIG. 7, when a transport target is collected from a node 211 having a collection position 203 of “18” and a node 211 of “3, 4, 8”, as illustrated in FIG. When the node 211 “4, 8” of the primary solution “→ 4 → 8 → 3 → 18” is exchanged, “18 → 8 → 4 → 3 → 18” is obtained as shown in FIG. 7B. A quadratic solution is generated.

  Further, when there are a plurality of collection operations in which the forklift moves from the collection position 203 to the collection position 203 via the flat / electric racks 201 and 202 in the collection plan of the primary solution, it is conveyed by the plurality of collection operations of the primary solution. The flat / electric racks 201 and 202 having the same target quantity are randomly exchanged, and a secondary solution is generated.

  Further, the flat / electric racks 201 and 202 having the same quantity to be transported are also randomly exchanged in the pickup operation of a plurality of forklifts, the number of forklifts used at a time is also randomly changed, and a plurality of The allocation of the flat / electric racks 201 and 202 is also changed at random.

  For example, as shown in FIG. 8, when a transport target is picked up by two forklifts from a node 211 whose collection position 203 is “18” and “3, 4, 8, 11”, FIG. As shown in FIG. 4, when some nodes 211 of the primary solution “18 → 11 → 18” “18 → 8 → 4 → 3 → 18” are exchanged, “18 → 11 → 8 → 18” “18” A quadratic solution of 4 → 3 → 18 ”is generated as data.

  When the primary solution and the secondary solution of the pickup plan are generated as described above, the movement distance of the pickup plan of the plurality of forklifts is converted into the movement time, and the total time obtained by adding the waiting time to the movement time. Calculated as an evaluation value (step E4).

  Needless to say, since the collecting operations of the plurality of forklifts are executed in parallel, the maximum required time among the times required for the plurality of forklifts becomes the evaluation value of the collection plan. For example, as shown in FIG. 6B, when the forklift of “Operator 1-3” performs the collection work in parallel, the maximum required time of “Operator 1” becomes the evaluation value.

  When the evaluation value between the primary solution and the secondary solution of the collection plan is calculated as described above, a difference value ΔI obtained by subtracting the evaluation value of the primary solution from the evaluation value of the secondary solution is calculated (step E5). For example, as shown in FIGS. 7A and 7B, a secondary solution “18 → 8 → 4 → 3 → 18” is generated from a primary solution “18 → 4 → 8 → 3 → 18”. Then, since the number of arcs 212 corresponding to the required time is reduced from “16” to “14”, the difference value ΔI becomes “−2”.

  If the difference value ΔI is a negative value as described above, the primary solution is replaced with the secondary solution (step E7). However, even if the difference value ΔI is not a negative value, “d <exp (ΔI / If T) (d is a uniform random number “0 ≦ d <1” and T is a predetermined variable) ”is satisfied (step E8), the primary solution is replaced with the secondary solution (step E7).

  When the processing operation from the generation of the secondary solution to the replacement of the primary solution as described above is repeated a predetermined number of times (steps E9 and E10), the above-described variable T is multiplied by a predetermined constant γ of “1” or less. Thus, the data is updated (step E11).

  As described above, each time the variable T is updated, the processing operation from the generation of the secondary solution data to the replacement of the primary solution is repeated a predetermined number of times (steps E3 to E10). If the primary solution is not replaced with the secondary solution even if the processing operation until the data update is repeated a predetermined number of times (steps E13 to E16), the primary solution is determined as a collection plan (step E18).

  However, even when the processing operation is not repeated up to a predetermined number of times when the primary solution is not replaced with the secondary solution, if the data update of the variable T is repeated up to the predetermined number of times (steps E12 and E17), the primary at that time The solution is finalized as a collection plan (step E18).

  When the collection plan is finalized as described above, as shown in FIG. 10, since the collection plan is output as data on the display 112 or the like, a plurality of forklift operators can collect the output collection plans. Each is confirmed, and in response to the collection plan, a collection operation for collecting a plurality of conveyance objects from the flat / electric racks 201 and 202 to the collection position 203 is executed in parallel.

[Effect of the embodiment]
In the data processing apparatus 100 according to the present embodiment, when the type and quantity of the conveyance target to be collected are input as data, a collection plan for collecting the conveyance target at the shortest distance is searched for data by the SA method, and the data is output. A plurality of forklifts can efficiently collect a plurality of objects to be transported in a shortest time corresponding to the data output collection plan.

  In addition, in the data processing apparatus 100 according to the present embodiment, when the physical arrangement of the flat / electric racks 201 and 202 is input, a path including the movement path 204 in which the conveyance time of the conveyance target by the forklift is converted into the movement distance. Since the chart 210 is generated as a data, it is possible to automatically generate the path chart 210 effective for the data generation of the collection plan.

  In particular, data is converted into a predetermined unit of arc 212 connected to the movement path 204 via the node 211, and the flat / electric racks 201 and 202 and the pickup position 203 are converted into the node 211 to be converted into the path diagram 210. Since the data is generated, it is possible to automatically generate the route diagram 210 that facilitates the generation of the data of the movement route 204 and the detection of the data of the movement distance.

  Further, the temporary inventory warehouse 200 of this embodiment includes a flat rack 201 that does not require a specific carry-out time for carrying-out work by a forklift and an electric rack 202 that requires a specific carry-out time. In the processing apparatus 100, when data is input for each electric rack 202 as well as the physical arrangement of the plurality of flat / electric racks 201 and 202, a route diagram 210 is generated from the data input physical arrangement and the output time. Therefore, it is possible to automatically generate data for the route diagram 210 in which the difference in the carry-out time of the flat / electric racks 201 and 202 is reflected.

  Further, in the route diagram 210 generated as described above, the movement route 204 communicating with the electric rack 202 and the like protrudes extremely outward, but in the data processing device 100 of this embodiment, it protrudes outward. Since the linear movement path 204 is bent and the path chart 210 is formed in a predetermined rectangular range, data display and data printing of the generated path chart 210 are easy.

  Moreover, in the flat rack 201, a plurality of forklifts can simultaneously carry out the unloading work, but in the electric rack 202, a plurality of forklifts cannot simultaneously carry out the unloading work. However, in the data processing apparatus 100 according to the present embodiment, when the physical arrangement of the plurality of flat / electric racks 201 and 202 and the availability of simultaneous work by a plurality of forklifts for each of the flat / electric racks 201 and 202 are input, Whether or not this is possible is given data for each of the flat / electric racks 201 and 202 in the path diagram 210.

  And since the collection plan is searched for data corresponding to the availability, it is possible to automatically prevent the generation of an inappropriate collection plan in which a plurality of forklifts move simultaneously to the position of the electric rack 202. . In particular, when the movement of a plurality of forklifts at the position of the electric rack 202 is detected, the order in which the movement path 204 is moved to the plurality of forklifts detected by the data is given by the FIFO rule, and the waiting time is set as data. The approach to the position of the electric rack 202 by a plurality of forklifts is accurately set in the collection plan.

  Then, since the travel distance of the collection plans of the plurality of forklifts is converted into the travel time and the collection plan that minimizes the total time obtained by adding the standby time is searched for, the electric rack 202 that requires a specific transport time is searched. In consideration of this, it is possible to reliably generate data for a collection plan that can efficiently collect a plurality of transport targets in a short time by using a plurality of forklifts.

  Further, the shortest path for each combination of the plurality of flat / electric racks 201 and 202 and one pickup position 203 is detected from the route diagram 210 by the Dijkstra method and registered, and the shortest path in which the data is registered. Since the collection plan is searched based on the data, it is possible to efficiently search for a collection plan for efficiently collecting a plurality of transport targets in the shortest time with simple data processing.

  Further, in the data processing apparatus 100 of the present embodiment, when searching for a collection plan by the SA method as described above, as a plurality of neighborhood searches, a combination of a 2-opt neighborhood and a random neighborhood is used to obtain data from a primary solution to a secondary solution. Since it is generated, it is possible to efficiently generate data of a secondary solution using an existing algorithm.

  In that case, even if a plurality of forklifts are used at the same time, the number of forklifts used at a time is also randomly changed, and the assignment of a plurality of flat / electric racks 201 and 202 to a plurality of forklifts is also randomly changed. In addition, it is possible to generate data for a collection plan in which parallel work by a plurality of forklifts is efficiently assembled.

[Disclosure of specific examples]
Here, the processing method actually executed by the present inventor will be briefly described below. First, in order to formulate a collection plan by a plurality of forklifts, the present inventor has defined various variables as follows. In addition, the code | symbol of the following description is not related with the code | symbol used in the flowchart of FIG.

N: set of nodes 211 N _i : set of nodes 211 of flat / electric racks 201 and 202 (N _i ∈ N)
V: set of forklifts m: identification number of forklift (m = 1 to 5 in this embodiment)
k: number of reciprocations of the forklift (in this embodiment, k = 1 to 4)
C _ij: the shortest distance from the "i" becomes the node 211 to the "j" becomes the node 211 w _i: number of the transport object for collection from "i" becomes the node 211 W: the transport object forklift can carry a time quantity p _i ^m : time when the forklift “m” enters the position of the electric rack 202 s _i ^m : transport time of the forklift “m” at the electric rack 202
i, j∈N
m∈V
It is. Next, the decision variable “x _{i, j, k} ^m ” was set as follows.

  And the quantity of the conveyance object which a forklift can convey at once is defined by the following conditional expressions.

  Further, the fact that a plurality of forklifts cannot move simultaneously at the position of the electric rack 202 is defined by the following conditional expression. Equation (3) means that the forklift of the next stage enters after the forklift of the foremost side is separated from the position of the electric rack 202, and Equation (4) indicates that the position of the electric rack 202 is at once. This means that there is only one forklift, and equation (5) means that there is only one forklift moving at the position of the electric rack 202 at a time.

The objective function for minimizing the required time “f _m ” for collecting a plurality of transport objects by a plurality of forklifts is defined as follows.

  Then, the inventor actually sets the number of repetitions of the processing operation from the generation of the secondary solution data to the replacement of the primary solution to “200 times (N = 200 in FIG. 11)”, and updates the data of the variable T. The simulation was executed with the number of repetitions being “500 times (M = 500 in FIG. 11)”, the variable T being “10”, and the constant γ being “0.96”. It was possible to generate data for a collection plan that ended in time.

  Further, when the number of forklifts used at one time was also simulated, as shown in FIG. 12, the time required for the collection work is not shortened as the number of forklifts increases depending on conditions. It was confirmed that the number of forklifts can be generated.

[Modification of Embodiment]
The present invention is not limited to the present embodiment, and various modifications are allowed without departing from the scope of the present invention. For example, in the above embodiment, the route diagram 210 is generated from the physical arrangement of the plurality of flat / electric racks 201 and 202, and each combination of the plurality of flat / electric racks 201 and 202 and one pickup position 203 is used. It is illustrated that the shortest path of the data is detected and the search of the collection plan from the collection request corresponding to the route chart 210 is performed by one data processing device 100. It is also possible to execute the data processing apparatus individually.

  Further, in the above embodiment, it is exemplified that a plurality of forklifts perform the collection work in parallel in the temporary inventory warehouse 200. However, for example, the data search for the collection plan according to the present plan is useful even when there is only one forklift. In addition, when there is one forklift, the waiting time in the electric rack 202 as described above does not occur, so there is no need for data processing for not positioning a plurality of forklifts on the electric rack 202 at the same time, and the evaluation value is also It is possible to set the travel distance instead of the required time.

  Furthermore, in the above embodiment, the temporary inventory warehouse 200 does not require a specific carry-out time for a carry-out operation, and a flat rack 201 that allows a plurality of forklifts to simultaneously carry out the carry-out work, and a plurality of forklifts that require a specific carry-out time simultaneously The electric rack 202 that cannot carry out the carry-out operation is exemplified as an inventory location, but the collection plan in the temporary inventory warehouse (not shown) having only one of the flat / electric racks 201 and 202 is exemplified. This plan can also be applied to the data search.

  Further, in the above embodiment, when data is input to the data processing apparatus 100 together with the physical arrangement of the plurality of flat / electric racks 201 and 202, the data processing apparatus 100 performs the unloading time of the electric rack 202. Is automatically converted into a moving distance and the route diagram 210 is generated as data. However, the data entry of the carry-out time as described above is not executed, and the operator manually corrects the generated route chart, thereby extending the movement route 204 to the electric rack 202 corresponding to the carry-out time. It is also possible to do.

  Furthermore, in the said form, it illustrated that the data processor 100 installed in the temporary inventory warehouse 200 searches data for the collection plan for the worker of a forklift. However, in an automated transport warehouse (not shown) that has an electronically controlled hoist or the like as the target transport means, it is also possible to collect the transport target by controlling the operation of the target transport means using the data collection search plan. is there.

  In the above embodiment, the data processing apparatus 100 generates the collection plan for efficiently collecting various transport targets from the plurality of flat / electric racks 201 and 202 to one collection position 203. For example, By the same data processing, it is also possible to generate data for a plan for efficiently transporting and storing various transport targets from a single collection position 203 to a plurality of flat / electric racks 201 and 202.

  Furthermore, in this embodiment, it is exemplified that various means are logically realized as various functions of the data processing apparatus 100 by the CPU 101 operating corresponding to the computer program stored in the RAM 104 or the like. However, each of these various means can be formed as unique hardware, and a part can be stored in the RAM 104 or the like as software and a part can be formed as hardware.

It is a schematic diagram which shows the logical structure of the data processor of one Embodiment of this invention. It is a schematic diagram which shows the internal structure of a route search means. It is a block diagram which shows the physical structure of a data processor. It is a top view which shows the physical structure of a temporary inventory warehouse. It is a schematic diagram which shows a route diagram. It is a Gantt chart which shows the relation of a forklift which is a plurality of object conveyance means in a collection plan. It is a schematic diagram which shows an example which produces | generates data of the secondary solution from the primary solution of a collection plan. It is a schematic diagram which shows an example which produces | generates data of the secondary solution from the primary solution of a collection plan. It is a flowchart which shows the data processing method in which a data processor produces | generates a path | route diagram data from the physical structure of a temporary inventory warehouse. It is a flowchart which shows the data processing method of the main routine in which a data processor produces | generates a collection plan from a collection request. It is a flowchart which shows the data processing method of the subroutine which searches data for a collection plan. It is a characteristic view which shows the relationship between the number of forklifts and the time required for the collection work.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Data processing apparatus 101 CPU which is the main body of computer
103 ROM as an information storage medium
104 RAM as an information storage medium
105 HDD as an information storage medium
106 FD, an information storage medium
108 CD-ROM as information storage medium
DESCRIPTION OF SYMBOLS 201 Flat rack which is a stock location 202 Electric rack which is a stock location 203 Pick-up position 204 Movement route 210 Route chart 211 Node 212 Arc 301 Map input means 302 Map generation means 303 Map registration means 304 Route detection means 305 Shortest registration means 311 Map Storage means 312 Inventory storage means 313 Condition storage means 314 Shortest storage means 316 Target input means 317 Inventory detection means 318 Route search means 319 Route output means 321 Initial generation means 322 Random change means 323 Evaluation calculation means 324 Difference calculation means 326 First replacement Means 327 Second replacement means 328 Operation control means 329 Variable update means 331 Processing control means 332 Result confirmation means 334 2 Opt proximity means 335 Random proximity means

Claims (2)

A data processing device for an automatic transport warehouse that generates data for a collection plan for collecting a plurality of types of transport targets in a distributed inventory in a plurality of inventory locations to a predetermined collection position by using a plurality of target transport means that can be moved simultaneously. Because
Map input means for inputting at least a physical arrangement of the inventory location and the pickup position;
A chart generating means for generating data from a path diagram including a moving path in which the transport time of the transport target by the target transport means is converted into a travel distance from the physical arrangement that has been input data;
And the earth view storage means,
Map registration means for registering data in the map storage means with the generated route chart;
Stock storage means for storing data on the transport target stocked for each stock location;
Condition storage means for storing the quantity of the transport target that can be transported by the target transport means at a time;
Target input means for inputting data of the type and quantity of the transport target to be collected at the pickup position;
Inventory detecting means for detecting data from the storage data of the inventory storing means for a plurality of the inventory locations where the transport target that has been input data is in stock;
With reference to the storage data of the condition storage means and the route chart, the collection plan for collecting the plurality of transported objects inputted in the shortest time from the plurality of inventory locations where the data is detected to the collection position is referred to as SA. A route search means for searching for data by (Simulated Annealing) method,
Route output means for outputting data of the collection plan searched for data;
The have,
There are the inventory locations where a plurality of the target transport means can simultaneously perform the unloading operation and the inventory locations where the plurality of target transport means cannot simultaneously perform the unloading operation,
The map input means is also configured to input data on the availability of simultaneous work by the plurality of target transport means for each inventory location together with the physical arrangement of the plurality of inventory locations,
The chart generation means also adds data for the availability for each inventory location of the route chart that generates data from the physical layout that has been input data,
The route search means corresponds to the availability of data assigned to each inventory location in the route chart, and moves the plurality of target transport means on the movement route to which simultaneous work is impossible. Detecting data, assigning the order of moving the movement route to the plurality of target transporting means detected by the FIFO (First In First Out) rule, setting the waiting time as data, and collecting plans for the plurality of target transporting means Data search is performed for the collection plan that minimizes the total time obtained by converting the travel distance of the travel time into the travel time and adding the waiting time.
Data processing equipment for automated transport warehouses . Generated by moving the storage rack so that the transport target is exposed when the transport target is unloaded by the target transport means and the flat rack on which the transport target is placed as the inventory location There is an electric rack that requires an unloading time for the target transport means to enter the gap of the storage rack and unload the transport target ,
The map input means, as well as the physical arrangement of a plurality of the inventory locations, the carry-out time for each electric rack is also input data,
The chart generating means converts the carry-out time inputted as data into a movement distance, and generates data of the route chart including a movement path including the movement distance from the movement distance and the physical arrangement inputted as data. The data processing apparatus for an automatic conveyance warehouse according to claim 1 .

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