Distributed killing network task allocation method and device

Abstract

The invention discloses a distributed killing network task allocation method and device. The method comprises the following steps: acquiring node information of a distributed killing network; the distributed killing network node information comprises first network node information, second network node information and third network node information; performing matrix construction processing on the distributed killing network node information to obtain initial node matrix information; the initial node matrix information comprises A * B * C initial node element value information; the initial node matrix information is a three-dimensional matrix; and performing transformation processing on the initial node matrix information to obtain target task allocation result information.

Description

Technical Field

[0001] The present invention relates to the technical field of task planning, and in particular to a distributed kill net task allocation method and device. Background Art

[0002] Task allocation is a key issue in combat mission planning. When an enemy target is discovered, it is necessary to assign tasks to each reconnaissance or action functional module in the combat system. In the traditional centralized kill chain, reconnaissance, action and other functional modules are often integrated on the same combat platform / weapon, and the task allocation performed is usually a binary allocation mode of "platform / weapon-target". The binary task allocation algorithms used mainly include auction algorithms, mixed integer linear programming, genetic algorithms, and task allocation algorithms based on deep learning. These algorithms can effectively solve various problems in binary task allocation, but cannot effectively solve the distributed kill network multi-task allocation modeling and solution problems that have emerged in recent years. Therefore, a distributed kill network task allocation method and device are provided to solve the exact solution to the kill network task allocation problem, and then solve the problem of how to allocate resources and tasks in the distributed kill network combat style, thereby optimizing resource allocation. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a distributed kill net task allocation method and device that is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0004] In order to solve the above technical problems, the first aspect of the embodiment of the present invention discloses a distributed kill net task allocation method, the method comprising:

[0005] Obtain distributed kill network node information; the distributed kill network node information includes first network node information, second network node information and third network node information; the first network node information includes A first node information; each of the first node information includes a first network node, a first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each of the second node information includes a second network node, a fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node;

[0006] Performing matrix construction processing on the distributed kill network node information to obtain initial node matrix information; the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix;

[0007] The initial node matrix information is transformed to obtain target task allocation result information.

[0008] A second aspect of an embodiment of the present invention discloses a distributed killnet task allocation device, the device comprising:

[0009] An acquisition module is used to acquire distributed kill network node information; the distributed kill network node information includes first network node information, second network node information and third network node information; the first network node information includes A first node information; each of the first node information includes a first network node, a first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each of the second node information includes a second network node, a fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node;

[0010] A first processing module is used to perform matrix construction processing on the distributed kill network node information to obtain initial node matrix information; the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix;

[0011] The second processing module is used to transform the initial node matrix information to obtain target task allocation result information.

[0012] The third aspect of the present invention discloses another distributed kill net task allocation device, the device comprising:

[0013] A memory storing executable program code;

[0014] a processor coupled to the memory;

[0015] The processor calls the executable program code stored in the memory to execute part or all of the steps in the distributed kill net task allocation method disclosed in the first aspect of the embodiment of the present invention.

[0016] The fourth aspect of the present invention discloses a computer-readable storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the distributed kill network task allocation method disclosed in the first aspect of the embodiment of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a flow chart of a distributed kill net task allocation method disclosed in an embodiment of the present invention;

[0019] Figure 2 It is a structural schematic diagram of a distributed kill net task allocation device disclosed in an embodiment of the present invention;

[0020] Figure 3 It is a structural schematic diagram of another distributed kill net task allocation device disclosed in an embodiment of the present invention;

[0021] Figure 4 It is a structural schematic diagram of an initialization matrix disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0024] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0025] The present invention discloses a distributed kill net task allocation method and device, which is conducive to finding an accurate solution to the kill net task allocation problem, and further solves the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation. Detailed descriptions are given below.

[0026] Embodiment 1

[0027] See also Figure 1 , Figure 1 1 is a flow chart of a distributed kill network task allocation method disclosed in an embodiment of the present invention. Figure 1 The distributed kill network task allocation method described is applied to a management system, such as a local server or a cloud server for management, and the embodiments of the present invention do not limit this. Figure 1 As shown, the distributed kill network task allocation method may include the following operations:

[0028] 101. Obtain distributed kill network node information.

[0029] In an embodiment of the present invention, the distributed killing network node information includes first network node information, second network node information and third network node information; the first network node information includes A first node information; each first node information includes a first network node, a first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each second node information includes a second network node, a fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node.

[0030] 102. Perform matrix construction processing on the distributed killing network node information to obtain initial node matrix information.

[0031] In the embodiment of the present invention, the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix.

[0032] 103. Perform transformation processing on the initial node matrix information to obtain target task allocation result information.

[0033] It should be noted that the first network node represents a reconnaissance node in the distributed kill network, the second network node represents an action node, and the third network node represents a target node.

[0034] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0035] In an optional embodiment, the above-mentioned matrix construction process is performed on the distributed kill network node information to obtain the initial node matrix information, including:

[0036] Get the initialization matrix information and node weight information;

[0037] Based on the initialization matrix information, node weight information and distributed kill network node information, the initial node matrix information is obtained.

[0038] like Figure 4 As shown, the matrix corresponding to the initialization matrix information is a three-dimensional matrix, and its expression is:

[0039]

[0040] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0041] In another optional embodiment, based on the initialization matrix information, the node weight information and the distributed kill network node information, the initial node matrix information is obtained, including:

[0042] For any initialization element value information in the initialization matrix information, first node information and second node information matching the coordinate information corresponding to the initialization element value information are selected from the distributed kill network node information to obtain first target node information and second target node information;

[0043] The matrix element value calculation model is used to calculate the initialization element value information and the node weight information to obtain the initial node element value information corresponding to the initialization element value information;

[0044] Among them, the matrix element value information is:

[0045] JZYabc =x1·(v1 a +v2 b )+x2·(d1 ac +d2 bc )+x3·(t1 ac +t2 bc );

[0046] In the formula, JZYSZ abc is the initial node element value information with coordinate information (a, b, c); x1, x2 and x3 are the first node weight, second node weight and third node weight in the node weight information respectively; v1 a , d1 ac and t1 ac They are respectively the first sub-target node information, the second sub-target node information and the third sub-target node information in the first target node information; v2 b , d2 bc and t2 bc It is the fourth sub-target node information, the fifth sub-target node information and the sixth sub-target node information in the second target node information.

[0047] It should be noted that the above-mentioned first node information and second node information matching the coordinate information corresponding to the initialization element value information are screened out from the distributed killing network node information to obtain the first target node information and the second target node information, and the first sub-node information, 1 second sub-node information and 1 third sub-node information are determined from the first sub-node information of the first node information, several second sub-node information and several third sub-node information, and the fourth sub-node information, 1 fifth sub-node information and 1 sixth sub-node information are determined from the fourth sub-node information, several fifth sub-node information and several sixth sub-node information of the second node information. For example, when the coordinate information corresponding to the initialization element value information is (2,3,1), the first sub-node information of the first node information is v12, and the second sub-node information includes d1 21 , d1 22 and d1 23 , the third child node information includes t1 21 、t1 22 and t1 23 , then according to the first coordinate element (2) and the third coordinate element (1) in the coordinate information corresponding to the initialization element value information, it can be determined that the first child node information corresponding to the first target node information is v12, and the second child node information is d1 21 , the third child node information is t1 21 , the second target node information can be determined in the same way.

[0048] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0049] In yet another optional embodiment, the initial node matrix information is transformed to obtain target task allocation result information, including:

[0050] The initial node matrix information is amplified to obtain first target node matrix information; the first target node matrix information is a three-dimensional matrix composed of a plurality of X planes, Y planes and Z planes arranged in sequence; the first target node element value information of the first target node matrix information contained in each X plane, Y plane and Z plane is consistent;

[0051] The first target node matrix information is transformed to obtain target task allocation result information.

[0052] It should be noted that if Figure 4 As shown, the three-dimensional matrix includes a number of X planes, Y planes and Z planes, and each coordinate point in each X plane, Y plane and Z plane corresponds to an element value information.

[0053] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0054] In yet another optional embodiment, the initial node matrix information is amplified to obtain the first target node matrix information, including:

[0055] Determine whether A, B and C are consistent and obtain a numerical judgment result;

[0056] When the numerical judgment result is yes, the initial node matrix information is determined to be the first target node matrix information;

[0057] When the result of the numerical judgment is no, the maximum value among A, B and C is determined as the target dimension;

[0058] Determine the maximum value of the initial node element value corresponding to the initial node element value information in the initial node matrix information as the amplified element value;

[0059] The initial node matrix information is expanded into a matrix of target dimension × target dimension × target dimension using the expanded element value as the newly added element, thereby obtaining the first target node matrix information.

[0060] It should be noted that the above-mentioned amplification processing of the initial node matrix information obtains the first target node matrix information, which is that the numbers of the first network nodes, the second network nodes, and the third network nodes in the known distributed killing network are A, B, and C respectively, and N is set to be the maximum value among A, B, and C, that is, N=max(A,B,C).

[0061] If A=B=C, then A=B=C=N;

[0062] If A, B and C are not completely equal, then N = max(A, B, C), and the dimension of the initial node matrix information is expanded from A×B×C to N×N×N to form a new matrix (first target node matrix information), and the cost value of the newly added element in the first target node matrix information is set to the maximum element value max(initial node matrix information) in the initial node matrix information. Thus, an N×N×N dimensional first target node matrix information is obtained (if A=B=C, then the initial node matrix information = the first target node matrix information; if A, B and C are not completely equal, the first target node matrix information has a dimension expansion compared to the initial node matrix information).

[0063] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0064] In an optional embodiment, the transformation process is performed on the first target node matrix information to obtain the target task allocation result information, including:

[0065] For any X-plane in the first target node matrix information, select the first target node element value corresponding to the minimum first target node element value information in the X-plane as the minimum X-plane value corresponding to the X-plane;

[0066] Subtract the minimum value of the X plane corresponding to the X plane from the first target node element value corresponding to all the first target node element value information in the X plane to obtain the first X plane corresponding to the X plane;

[0067] For any Y plane in the first target node matrix information, select the first target node element value corresponding to the minimum first target node element value information in the Y plane as the minimum Y plane value corresponding to the Y plane;

[0068] Subtract the minimum value of the Y plane corresponding to the Y plane from the first target node element value corresponding to all the first target node element value information in the Y plane to obtain the first Y plane corresponding to the Y plane;

[0069] For any Z plane in the first target node matrix information, select the first target node element value corresponding to the smallest first target node element value information in the Z plane as the Z plane minimum value corresponding to the Z plane;

[0070] Subtract the Z plane minimum value corresponding to the Z plane from the first target node element value corresponding to all the first target node element value information in the Z plane to obtain the first Z plane corresponding to the Z plane;

[0071] Substituting all first X planes, first Y planes and first Z planes for the corresponding X planes, Y planes and Z planes in the first target node matrix information in sequence to obtain second target node matrix information;

[0072] The second target node matrix information is optimized and calculated to obtain target task allocation result information.

[0073] It should be noted that the above subtracting the current minimum element of each plane from each X, Y, and Z plane in turn requires a total of N^3 operations. After the operation, each of the first X plane, the first Y plane, and the first Z plane has at least one zero element.

[0074] It should be noted that the zero element indicates that the second target node element value corresponding to the second target node element value information in the second target node matrix information is 0.

[0075] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0076] In another optional embodiment, the second target node matrix information is optimized and calculated to obtain target task allocation result information, including:

[0077] Optimizing the second target node matrix information to obtain the target task node matrix information;

[0078] The target task node matrix information and the first target node matrix information are calculated and processed by using the task allocation calculation model to obtain target task allocation result information;

[0079] Among them, the task allocation calculation model is:

[0080]

[0081] Where RWFP is the target task allocation result information; JZYSZ ijk is the element value information of the first target node with coordinate information (i, j, k) in the first target node matrix information; RWJD ijkis the target task node element value information with coordinate information (i, j, k) in the target task node matrix information; N is the target dimension.

[0082] In this optional embodiment, as an optional implementation, the above-mentioned optimization processing of the second target node matrix information to obtain the target task node matrix information includes:

[0083] Performing X-plane verification on the second target node matrix information;

[0084] The X-plane verification of the second target node matrix information includes:

[0085] Check the second target node matrix information on the first X plane one by one. When there is only one unmarked zero element in the first X plane, mark the second target node element value information with the symbol O, and then mark the other unmarked zero elements in the first Y plane and the first Z plane where the second target node element value information marked with the symbol O is located with the symbol *.

[0086] Repeating the X-plane check of the second target node matrix information until each first X-plane has no unmarked zero elements or at least two unmarked zero elements;

[0087] Perform Y-plane verification on the second target node matrix information;

[0088] The X-plane verification of the second target node matrix information includes:

[0089] Check the second target node matrix information on the first Y plane one by one. When there is only one unmarked zero element on the first Y plane, mark the second target node element value information with the symbol O, and then mark the other unmarked zero elements in the first X plane and the first Z plane where the second target node element value information marked with the symbol O is located with the symbol *.

[0090] Repeating the Y-plane check of the second target node matrix information until each first Y-plane has no unmarked zero elements or at least two unmarked zero elements;

[0091] Performing Z-plane verification on the second target node matrix information;

[0092] The Z-plane verification of the second target node matrix information includes:

[0093] Check the second target node matrix information on the first Z plane one by one. When there is only one unmarked zero element on the first Z plane, mark the second target node element value information with the symbol O, and then mark the other unmarked zero elements in the first X plane and the first Y plane where the second target node element value information marked with the symbol O is located with the symbol *.

[0094] Repeating the Z-plane check of the second target node matrix information until each first Z plane has no unmarked zero elements or at least two unmarked zero elements;

[0095] Determine whether the second target node matrix information satisfies the first verification condition, and obtain the first condition judgment result;

[0096] When the result of the first condition judgment is yes, the second target node element value corresponding to the second target node element value information marked by the symbol O in the second target node matrix information is determined to be 0, and the second target node element value corresponding to the second target node element value information not marked by the symbol O is determined to be 1, to obtain the target task node matrix information;

[0097] When the first condition judgment result is no, judging whether the second target node matrix information satisfies the second verification condition, and obtaining the second condition judgment result;

[0098] When the result of the second condition judgment is yes, for any first X plane in the second target node matrix information, it is judged whether the unmarked zero elements in the first X plane are greater than or equal to 2, and a first zero element judgment result is obtained;

[0099] When the result of the first zero element judgment is yes, a zero element in the first X-plane that has not been marked is randomly marked with the symbol O, and other zero elements that have not been marked are marked with the symbol *;

[0100] When the first zero element judgment result is no, the judgment process corresponding to the first zero element judgment result is terminated;

[0101] For any first Y plane in the second target node matrix information, determine whether the unmarked zero elements in the first Y plane are greater than or equal to 2, and obtain a second zero element determination result;

[0102] When the result of the second zero element judgment is yes, a zero element in the first Y plane that has not been marked is randomly marked with the symbol O, and other zero elements that have not been marked are marked with the symbol *;

[0103] When the second zero element judgment result is no, the judgment process corresponding to the second zero element judgment result is terminated;

[0104] For any first Z plane in the second target node matrix information, determine whether the unmarked zero elements in the first Z plane are greater than or equal to 2, and obtain a third zero element determination result;

[0105] When the result of the third zero element judgment is yes, a zero element that has not been marked in the first Z plane is randomly marked with the symbol O, and other zero elements that have not been marked are marked with the symbol *;

[0106] When the third zero element judgment result is no, the judgment process corresponding to the third zero element judgment result is ended;

[0107] Triggering execution of X-plane verification of the second target node matrix information;

[0108] When the result of the second condition judgment is no, all first X planes in the second target node matrix information that do not contain the second target node element value information marked with the symbol O are marked with the symbol √;

[0109] Mark the first Y plane and the first Z plane where all zero elements in the first X plane marked by the symbol √ are located with the symbol √;

[0110] Mark the first X plane where the second target node element value information marked by the symbol O in all the first Y planes marked by the symbol √ and the first Z plane is located with the symbol √;

[0111] Determine the minimum value as the correction element value from the second target node element values ​​corresponding to all the second target node element value information of all the unlabeled planes;

[0112] Subtract the correction element value from the second target node element value corresponding to all the second target node element value information of the first X plane marked with the symbol √;

[0113] Add the correction element value to the second target node element values ​​corresponding to all the second target node element value information of the first Y plane and the first Z plane marked with the symbol √;

[0114] Trigger execution of X-plane check on the second target node matrix information.

[0115] It should be noted that the unmarked planes include a first X plane not marked with a √ symbol, a first Y plane not marked with a √ symbol, and a first Z plane not marked with a √ symbol.

[0116] It should be noted that the addition of the correction element value to the second target node element values ​​corresponding to all the second target node element value information of the first Y plane and the first Z plane marked with the symbol √ can avoid the negative elements appearing in the first X plane marked with the symbol √.

[0117] It should be noted that the above-mentioned first verification condition is that each first X plane has a second target node element value information marked with the symbol O, each first Y plane has a second target node element value information marked with the symbol O, each first Z plane has a second target node element value information marked with the symbol O, and the number of second target node element value information marked with the symbol O is equal to N.

[0118] It should be noted that the second verification condition is that the second target node matrix information has unlabeled zero elements, and the plane where the unlabeled zero elements are located has at least two unlabeled zero elements. Further, the plane includes any one or more of the first X plane, the first Y plane or the first Z plane.

[0119] It should be noted that the unmarked zero element represents a zero element that is not marked by the symbol O or the symbol *.

[0120] It can be seen that implementing the distributed kill net task allocation method described in the embodiment of the present invention is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0121] Embodiment 2

[0122] See also Figure 2 , Figure 2 Schematic diagram of a distributed kill net task allocation device disclosed in an embodiment of the present invention. Figure 2 The described device can be applied to a warehouse management system, such as a local server or cloud server for warehouse logistics distributed kill network task allocation management, etc., and the embodiments of the present invention are not limited thereto. Figure 2 As shown, the device may include:

[0123] The acquisition module 201 is used to acquire the node information of the distributed killing network; the node information of the distributed killing network includes the first network node information, the second network node information and the third network node information; the first network node information includes A first node information; each first node information includes the first network node, the first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each second node information includes the second network node, the fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node;

[0124] The first processing module 202 is used to perform matrix construction processing on the distributed kill network node information to obtain initial node matrix information; the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix;

[0125] The second processing module 203 is used to transform the initial node matrix information to obtain target task allocation result information.

[0126] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0127] In another optional embodiment, Figure 2 As shown, the first processing module 202 performs matrix construction processing on the distributed kill network node information to obtain initial node matrix information, including:

[0128] Get the initialization matrix information and node weight information;

[0129] Based on the initialization matrix information, node weight information and distributed kill network node information, the initial node matrix information is obtained.

[0130] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0131] In yet another optional embodiment, Figure 2 As shown, the first processing module 202 obtains initial node matrix information based on the initialization matrix information, the node weight information and the distributed kill network node information, including:

[0132] For any initialization element value information in the initialization matrix information, first node information and second node information matching the coordinate information corresponding to the initialization element value information are selected from the distributed kill network node information to obtain first target node information and second target node information;

[0133] The matrix element value calculation model is used to calculate the initialization element value information and the node weight information to obtain the initial node element value information corresponding to the initialization element value information;

[0134] Among them, the matrix element value information is:

[0135] JZY abc=x1·(v1 a +v2 b )+x2·(d1 ac +d2 bc )+x3·(t1 ac +t2 bc );

[0136] In the formula, JZYSZ abc is the initial node element value information with coordinate information (a, b, c); x1, x2 and x3 are the first node weight, second node weight and third node weight in the node weight information respectively; v1 a , d1 ac and t1 ac They are respectively the first sub-target node information, the second sub-target node information and the third sub-target node information in the first target node information; v2 b , d2 bc and t2 bc It is the fourth sub-target node information, the fifth sub-target node information and the sixth sub-target node information in the second target node information.

[0137] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0138] In yet another optional embodiment, Figure 2 As shown, the second processing module 203 transforms the initial node matrix information to obtain target task allocation result information, including:

[0139] The initial node matrix information is amplified to obtain first target node matrix information; the first target node matrix information is a three-dimensional matrix composed of a plurality of X planes, Y planes and Z planes arranged in sequence; the first target node element value information of the first target node matrix information contained in each X plane, Y plane and Z plane is consistent;

[0140] The first target node matrix information is transformed to obtain target task allocation result information.

[0141] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0142] In yet another optional embodiment, Figure 2As shown, the second processing module 203 performs an amplification process on the initial node matrix information to obtain the first target node matrix information, including:

[0143] Determine whether A, B and C are consistent and obtain a numerical judgment result;

[0144] When the numerical judgment result is yes, the initial node matrix information is determined to be the first target node matrix information;

[0145] When the result of the numerical judgment is no, the maximum value among A, B and C is determined as the target dimension;

[0146] Determine the maximum value of the initial node element value corresponding to the initial node element value information in the initial node matrix information as the amplified element value;

[0147] The initial node matrix information is expanded into a matrix of target dimension × target dimension × target dimension using the expanded element value as the newly added element, thereby obtaining the first target node matrix information.

[0148] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0149] In yet another optional embodiment, Figure 2 As shown, the second processing module 203 transforms the first target node matrix information to obtain target task allocation result information, including:

[0150] For any X-plane in the first target node matrix information, select the first target node element value corresponding to the minimum first target node element value information in the X-plane as the minimum X-plane value corresponding to the X-plane;

[0151] Subtract the minimum value of the X plane corresponding to the X plane from the first target node element value corresponding to all the first target node element value information in the X plane to obtain the first X plane corresponding to the X plane;

[0152] For any Y plane in the first target node matrix information, select the first target node element value corresponding to the minimum first target node element value information in the Y plane as the minimum Y plane value corresponding to the Y plane;

[0153] Subtract the minimum value of the Y plane corresponding to the Y plane from the first target node element value corresponding to all the first target node element value information in the Y plane to obtain the first Y plane corresponding to the Y plane;

[0154] For any Z plane in the first target node matrix information, select the first target node element value corresponding to the smallest first target node element value information in the Z plane as the Z plane minimum value corresponding to the Z plane;

[0155] Subtract the Z plane minimum value corresponding to the Z plane from the first target node element value corresponding to all the first target node element value information in the Z plane to obtain the first Z plane corresponding to the Z plane;

[0156] Substituting all first X planes, first Y planes and first Z planes for the corresponding X planes, Y planes and Z planes in the first target node matrix information in sequence to obtain second target node matrix information;

[0157] The second target node matrix information is optimized and calculated to obtain target task allocation result information.

[0158] It can be seen that implementation Figure 2 The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0159] In yet another optional embodiment, Figure 2 As shown, the second processing module 203 performs optimization calculation processing on the second target node matrix information to obtain target task allocation result information, including:

[0160] Optimizing the second target node matrix information to obtain the target task node matrix information;

[0161] The target task node matrix information and the first target node matrix information are calculated and processed by using the task allocation calculation model to obtain target task allocation result information;

[0162] Among them, the task allocation calculation model is:

[0163]

[0164] Where RWFP is the target task allocation result information; HZYSZ ijk is the element value information of the first target node with coordinate information (i, j, k) in the first target node matrix information; RWJD ijk is the target task node element value information with coordinate information (i, j, k) in the target task node matrix information; N is the target dimension.

[0165] It can be seen that implementation Figure 2The described distributed kill net task allocation device is conducive to finding an accurate solution to the kill net task allocation problem, and then solving the problem of how to allocate resources and tasks in the distributed kill net combat style, thereby optimizing resource allocation.

[0166] Embodiment 3

[0167] See also Figure 3 , Figure 3 : is a structural diagram of another distributed kill net task allocation device disclosed in an embodiment of the present invention. Figure 3 The described device can be applied to a warehouse management system, such as a local server or cloud server for warehouse logistics distributed kill network task allocation management, etc., and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the device may include:

[0168] A memory 301 storing executable program codes;

[0169] a processor 302 coupled to the memory 301;

[0170] The processor 302 calls the executable program code stored in the memory 301 to execute the steps in the distributed kill net task allocation method described in the first embodiment.

[0171] Embodiment 4

[0172] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the distributed killnet task assignment method described in the first embodiment.

[0173] Embodiment 5

[0174] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the distributed kill net task allocation method described in the first embodiment.

[0175] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0176] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0177] Finally, it should be noted that the distributed kill net task allocation method and device disclosed in the embodiments of the present invention disclose only the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed kill net task allocation method, characterized in that: The method comprises: Obtain distributed kill network node information; the distributed kill network node information includes first network node information, second network node information and third network node information; the first network node information includes A first node information; each of the first node information includes a first network node, a first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each of the second node information includes a second network node, a fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node; Performing matrix construction processing on the distributed kill network node information to obtain initial node matrix information; the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix; The initial node matrix information is transformed to obtain target task allocation result information.

2. The distributed kill net task allocation method according to claim 1 is characterized in that: The matrix construction process is performed on the distributed kill network node information to obtain initial node matrix information, including: Get the initialization matrix information and node weight information; Based on the initialization matrix information, the node weight information and the distributed kill network node information, initial node matrix information is obtained.

3. The distributed kill net task allocation method according to claim 2 is characterized in that: The obtaining of initial node matrix information based on the initialization matrix information, the node weight information and the distributed kill network node information includes: For any initialization element value information in the initialization matrix information, the first node information and the second node information matching the coordinate information corresponding to the initialization element value information are screened out from the distributed kill network node information to obtain the first target node information and the second target node information; The matrix element value calculation model is used to calculate the initialization element value information and the node weight information to obtain the initial node element value information corresponding to the initialization element value information; The matrix element value information is: <h2 style=";text-align:left;direction:ltr">JZYSZ<h2 style=";text-align:left;direction:ltr"> abc <h2 style=";text-align:left;direction:ltr"> =x1·(v1<h2 style=";text-align:left;direction:ltr"> a <h2 style=";text-align:left;direction:ltr"> +v2<h2 style=";text-align:left;direction:ltr"> b <h2 style=";text-align:left;direction:ltr"> )+x2·(d1<h2 style=";text-align:left;direction:ltr"> ac <h2 style=";text-align:left;direction:ltr"> +j2<h2 style=";text-align:left;direction:ltr"> bc <h2 style=";text-align:left;direction:ltr"> )+x3·(t1<h2 style=";text-align:left;direction:ltr"> ac <h2 style=";text-align:left;direction:ltr"> +t2<h2 style=";text-align:left;direction:ltr"> bc <h2 style=";text-align:left;direction:ltr"> ); In the formula, JZYSZ abc is the initial node element value information with coordinate information (a, b, c); x1, x2 and x3 are respectively the first node weight, the second node weight and the third node weight in the node weight information; v1 a , d1 ac and t1 ac v2 are respectively the first sub-target node information, the second sub-target node information and the third sub-target node information in the first target node information; b , d2 bc and t2 bc It is the fourth sub-target node information, the fifth sub-target node information and the sixth sub-target node information in the second target node information.

4. The distributed kill net task allocation method according to claim 1, characterized in that: The transforming process of the initial node matrix information to obtain target task allocation result information includes: The initial node matrix information is amplified to obtain first target node matrix information; the first target node matrix information is a three-dimensional matrix composed of a plurality of X planes, Y planes and Z planes arranged in sequence; the first target node element value information of the first target node matrix information contained in each of the X planes, the Y planes and the Z planes is consistent; The first target node matrix information is transformed to obtain target task allocation result information.

5. The distributed kill net task allocation method according to claim 4 is characterized in that: The amplifying process is performed on the initial node matrix information to obtain the first target node matrix information, including: Determine whether A, B and C are consistent, and obtain a numerical determination result; When the numerical judgment result is yes, determining the initial node matrix information as the first target node matrix information; When the numerical judgment result is no, determining the maximum value among A, B and C as the target dimension; Determine the maximum value of the initial node element value corresponding to the initial node element value information in the initial node matrix information as the augmented element value; The initial node matrix information is expanded into a matrix of the target dimension×the target dimension×the target dimension with the expanded element value as the newly added element, so as to obtain the first target node matrix information.

6. The distributed kill net task allocation method according to claim 4 is characterized in that: The transforming process of the first target node matrix information to obtain target task allocation result information includes: For any of the X planes in the first target node matrix information, selecting the first target node element value corresponding to the smallest first target node element value information in the X plane as the X plane minimum value corresponding to the X plane; Subtract the X-plane minimum value corresponding to the X-plane from the first target node element values ​​corresponding to all the first target node element value information in the X-plane to obtain a first X-plane corresponding to the X-plane; For any of the Y planes in the first target node matrix information, select the first target node element value corresponding to the smallest first target node element value information in the Y plane as the Y plane minimum value corresponding to the Y plane; Subtract the minimum value of the Y plane corresponding to the Y plane from the first target node element value corresponding to all the first target node element value information in the Y plane to obtain a first Y plane corresponding to the Y plane; For any of the Z planes in the first target node matrix information, select the first target node element value corresponding to the smallest first target node element value information in the Z plane as the Z plane minimum value corresponding to the Z plane; Subtract the Z-plane minimum value corresponding to the Z-plane from the first target node element values ​​corresponding to all the first target node element value information in the Z-plane to obtain a first Z-plane corresponding to the Z-plane; Substituting the first X plane, the first Y plane and the first Z plane in sequence for the corresponding X plane, the Y plane and the Z plane in the first target node matrix information, to obtain second target node matrix information; The second target node matrix information is optimized and calculated to obtain target task allocation result information.

7. The distributed kill net task allocation method according to claim 6 is characterized in that: The optimizing calculation process of the second target node matrix information to obtain target task allocation result information includes: Optimizing the second target node matrix information to obtain target task node matrix information; Using a task allocation calculation model to calculate and process the target task node matrix information and the first target node matrix information to obtain target task allocation result information; Wherein, the task allocation calculation model is: Where RWFP is the target task allocation result information; JZYSZ ijk is the element value information of the first target node with coordinate information (i, j, k) in the first target node matrix information; RWJD ijk It is the target task node element value information with coordinate information (i, j, k) in the target task node matrix information; N is the target dimension.

8. A distributed kill net task allocation device, characterized in that: The device comprises: An acquisition module is used to acquire distributed kill network node information; the distributed kill network node information includes first network node information, second network node information and third network node information; the first network node information includes A first node information; each of the first node information includes a first network node, a first sub-node information, a plurality of second sub-node information and a plurality of third sub-node information; the second network node information includes B second node information; each of the second node information includes a second network node, a fourth sub-node information, a plurality of fifth sub-node information and a plurality of sixth sub-node information; the third network node information includes C third network nodes; the second sub-node information represents the distance from the first network node to the third network node; the third sub-node information represents the time of movement from the first network node to the third network node; the fifth sub-node information represents the distance from the second network node to the third network node; the sixth sub-node information represents the time of movement from the second network node to the third network node; A first processing module is used to perform matrix construction processing on the distributed kill network node information to obtain initial node matrix information; the initial node matrix information includes A×B×C initial node element value information; the initial node matrix information is a three-dimensional matrix; The second processing module is used to transform the initial node matrix information to obtain target task allocation result information.

9. A distributed kill net task allocation device, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the distributed kill net task allocation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the distributed kill net task allocation method according to any one of claims 1-7.

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