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A novel genetic algorithm for the synthetical sensor-weapon-target assignment problem.

genetic algorithm for weapon target assignment problem

1. Introduction

2. problem analysis and formulation, 2.1. existing work of the s-wta problem, 2.1.1. framework a: the independent s-wta framework, 2.1.2. framework b: the dependent s-wta framework-i, 2.1.3. framework c: the dependent s-wta framework-ii, 2.2. the improved s-wta model, 2.2.1. the proposed s-wta model, 2.2.2. behaviors of the proposed gain factor σ, 3. description of the proposed method, 3.1. chromosome encoding, 3.2. population initialization.

Initialization
The number of sensors is M. The number of weapons is W. The number of targets is N. The matrix of the probability of detecting and tracking the targets by the sensors is . The matrix of the probability of destroying the targets by the weapons is . The maximum sensor cost of each target is . The maximum weapon cost of each target is . The threat value of each target is .
The initialized population . to to M . each target t as . as . to N to the original value. to W . each target t as . as . to N and

3.3. Evolutionary Operations

3.4. repair operations, 3.4.1. r-sta operation.

R-STA operation
The chromosome that need to be repaired is . The matrix of the probability of detecting and tracking the targets by the sensors is . The maximum sensor cost for target are . The threat value of each target is .
The repaired chromosome . as . ( ) . . as . each in each sensor s which is assigned to in for which the corresponding is the largest.

3.4.2. R-WTA Operation

R-WTA operation
The chromosome in which the R-STA operation has been performed is . The matrix of the probability of destroying the targets by the weapons is . The maximum weapon cost for target are . The threat value of each target is .
The repaired chromosome . as . as . ( ) or ( and ) . . as . each in each weapon w which is assigned to in for which the corresponding is the largest.

3.5. The Framework of GA-SWTA

GA-SWTA
Max generation: . Population size: . Crossover probability: . Mutation probability: . Other necessary scenario information of S-WTA problem.
The best individual . Generate an initial population by the proposed initialization method. Meanwhile, . A proportion of population X are selected as a new generation by some specific selection method. For do Generate a random number , if , randomly select an individual in , then perform the crossover operator on and to generate two new individuals as and . Generate a random number , if , randomly select an individual in , then perform the mutation operator on it to generate a new individual . Perform the proposed R-STA operation and R-WTA operation for the reproduced population . Let . Calculate the fitness for all the individuals in , then select the best individuals as the new generation X. , then go to Step 2. If reaches , output the best individual .

4. Experimental Studies

4.1. comparison algorithms, 4.2. experimental settings, 4.3. experiments on comparison algorithms, 4.4. experiments on initialization, 4.5. experiments on repair operations, 5. conclusions, author contributions, acknowledgments, conflicts of interest.

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Click here to enlarge figure

:The threat value of the kth target.
:The benefit of assigning ith sensor to kth target.
:The benefit of assigning jth weapon to kth target.
:The benefit of assigning th sensor–weapon pair to kth target.
:The benefit of assigning ith sensor and jth weapon to kth target.
:The kill probability that the weapon j against target k.
:The detection and tracking probability that the sensor i against target k.
:The kill probability that the weapon j against target k under the detection and tracking of sensor i.
:The sensor detection decision variable (if the ith sensor detects kth target ; otherwise, ).
:The sensor guidance decision variable (if the ith sensor guides the jth weapon ; otherwise, ).
:The sensor assignment decision variable (if the ith sensor is assigned to kth target ; otherwise, ).
:The weapon assignment decision variable (if the jth weapon is assigned to kth target ; otherwise, ).
:The sensor–weapon assignment decision variable (if the th sensor–weapon pair is assigned to kth target ; otherwise, , ).
:The sensor and weapon platform assignment decision variable (if the ith sensor and jth weapon platform are assigned to kth target ; otherwise, ).
FunctionVariable
00.76160.9640.99510.9993
00.7616 0.964 0.9951 0.9993
InstanceMWNInstanceMWN
No. 1543No. 14262317
No. 2457No. 15242221
No. 3666No. 16282319
No. 4988No. 17231930
No. 510712No. 18252028
No. 613119No. 19404040
No. 7171412No. 20625030
No. 8191415No. 21677254
No. 9151821No. 22857267
No. 10192316No. 231009080
No. 11202215No. 24150130120
No. 12211820No. 25180170160
No. 13202823

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Li, X.; Zhou, D.; Yang, Z.; Pan, Q.; Huang, J. A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem. Appl. Sci. 2019 , 9 , 3803. https://doi.org/10.3390/app9183803

Li X, Zhou D, Yang Z, Pan Q, Huang J. A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem. Applied Sciences . 2019; 9(18):3803. https://doi.org/10.3390/app9183803

Li, Xiaoyang, Deyun Zhou, Zhen Yang, Qian Pan, and Jichuan Huang. 2019. "A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem" Applied Sciences 9, no. 18: 3803. https://doi.org/10.3390/app9183803

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Weapon-target assignment problem: exact and approximate solution algorithms

  • Original Research
  • Published: 13 January 2022
  • Volume 312 , pages 581–606, ( 2022 )

Cite this article

genetic algorithm for weapon target assignment problem

  • Alexandre Colaers Andersen 1 ,
  • Konstantin Pavlikov   ORCID: orcid.org/0000-0002-3345-5058 1 &
  • Túlio A. M. Toffolo 2  

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The Weapon-Target Assignment (WTA) problem aims to assign a set of weapons to a number of assets (targets), such that the expected value of survived targets is minimized. The WTA problem is a nonlinear combinatorial optimization problem known to be NP-hard. This paper applies several existing techniques to linearize the WTA problem. One linearization technique (Camm et al. in Oper Res 50(6):946–955, 2002) approximates the nonlinear terms of the WTA problem via convex piecewise linear functions and provides heuristic solutions to the WTA problem. Such approximation problems are, though, relatively easy to solve from the computational point of view even for large-scale problem instances. Another approach proposed by O’Hanley et al. (Eur J Oper Res 230(1):63–75, 2013) linearizes the WTA problem exactly at the expense of incorporating a significant number of additional variables and constraints, which makes many large-scale problem instances intractable. Motivated by the results of computational experiments with these existing solution approaches, a specialized new exact solution approach is developed, which is called branch-and-adjust. The proposed solution approach involves the compact piecewise linear convex under-approximation of the WTA objective function and solves the WTA problem exactly. The algorithm builds on top of any existing branch-and-cut or branch-and-bound algorithm and can be implemented using the tools provided by state-of-the-art mixed integer linear programming solvers. Numerical experiments demonstrate that the proposed specialized algorithm is capable of handling very large scale problem instances with up to 1500 weapons and 1000 targets, obtaining solutions with optimality gaps of up to \(2.0\%\) within 2 h of computational runtime.

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For more information concerning the callback functions, the reader is directed to IBM and ILOG ( 2020 ).

Source code available at https://github.com/tuliotoffolo/wta .

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Andersen, A.C., Pavlikov, K. & Toffolo, T.A.M. Weapon-target assignment problem: exact and approximate solution algorithms. Ann Oper Res 312 , 581–606 (2022). https://doi.org/10.1007/s10479-022-04525-6

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  • Guo H (2022) Research on Target Assignment of Soft and Hard Weapons under Fire Compatibility Constraints 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) 10.1109/ITAIC54216.2022.9836551 (583-587) Online publication date: 17-Jun-2022 https://doi.org/10.1109/ITAIC54216.2022.9836551
  • Yang Y Yan M Liu Z Wei Z (2022) Opposition-based Memetic Algorithm for the Shared Weapon Target Assignment Problem 2022 China Automation Congress (CAC) 10.1109/CAC57257.2022.10056059 (1951-1956) Online publication date: 25-Nov-2022 https://doi.org/10.1109/CAC57257.2022.10056059
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  • DOI: 10.1109/IITA.2007.48
  • Corpus ID: 6073708

Immune Genetic Algorithm for Weapon-Target Assignment Problem

  • Gao Shang , Zhang Zai-yue , +1 author Cao Cun-gen
  • Published in Intelligent Information… 2 December 2007
  • Computer Science, Engineering

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15 Citations

Weapon target assignment with combinatorial optimization techniques, hybrid nested partition method with intelligent greedy search for solving weapon target assignment problem, string- and permutation-coded genetic algorithms for the static weapon-target assignment problem, a heuristic and metaheuristic approach to the static weapon target assignment problem, the weapon-target assignment problem, cooperative dynamic weapon-target assignment algorithm of multiple missiles based on networks, real-time heuristics and metaheuristics for static and dynammic weapon target assignments.

  • Highly Influenced

A bi-objective dynamic collaborative task assignment under uncertainty using modified MOEA/D with heuristic initialization

Expert systems with applications, mixed-integer linear programming model by linear approximation for a strike package-to-target assignment problem, 14 references, a genetic algorithm with domain knowledge for weapon‐target assignment problems, an immunity-based ant colony optimization algorithm for solving weapon-target assignment problem, efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics, solving weapon-target assignment problem by particle swarm optimization algorithm, a novel genetic algorithm based on immunity, a neural network-based optimization algorithm for the static weapon-target assignment problem, survey of the research on dynamic weapon-target assignment problem, direct laser sintering of a copper-based alloy for creating three-dimensional metal parts, recursively generated b-spline surfaces on arbitrary topological meshes, related papers.

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IMAGES

  1. (PDF) A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem

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  2. A genetic algorithm with domain knowledge for weapon‐target assignment problems: Journal of the

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  3. Genetic Algorithm

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  4. Solved The assignment is to start implementing a Genetic

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  5. Figure 10 from An Intelligent Algorithm for Solving Weapon-Target Assignment Problem: DDPG-DNPE

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COMMENTS

  1. Improved Genetic Algorithm for Weapon Target Assignment Problem

    Since the end of last century, intelligent optimization algorithm has been developing vigorously with the maturity of computer technology. Among them, genetic algorithm (GA) is the earliest and most mature optimization algorithm, and has been well applied in solving weapon target assignment (WTA) problem. In this paper, the implementation of GA is introduced. Aiming at the defect that ...

  2. A genetic algorithm for weapon target assignment problem

    Abstract. Weapon target assignment (WTA) problem is the problem of assigning weapons to targets with the objective of minimizing the expected damage of targets. In this work, a GA with a novel ...

  3. A genetic algorithm for weapon target assignment problem

    Weapon target assignment (WTA) problem is the problem of assigning weapons to targets with the objective of minimizing the expected damage of targets. In this work, a GA with a novel crossover operator is proposed for the particular WTA problem. ... "Efficiently solving general weapon-target assignment problem by genetic algorithms with genetic ...

  4. A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target

    The sensor-weapon-target assignment (S-WTA) problem is a crucial decision issue in C4ISR. The cooperative engagement capability (CEC) of sensors and weapons depends on the S-WTA schemes, which can greatly affect the operational effectiveness. In this paper, a mathematical model based on the synthetical framework of the S-WTA problem is established, combining the dependent and independent ...

  5. PDF Efficiently solving general weapon-target assignment problem by genetic

    Assignment Problem by Genetic Algorithms With Greedy Eugenics Zne-Jung Lee, Shun-Feng Su, Member, IEEE, and Chou-Yuan Lee ... LEE et al.: EFFICIENTLY SOLVING GENERAL WEAPON-TARGET ASSIGNMENT ...

  6. A genetic algorithm for weapon target assignment problem

    ICGA. 1985. 1,223. A GA with a novel crossover operator is proposed for the particular WTA problem to use a benefit level to identify good genes and the proposed algorithm outperforms its competitors on all test problems. Weapon target assignment (WTA) problem is the problem of assigning weapons to targets with the objective of minimizing the ...

  7. The Weapon-Target Assignment Problem

    Research addressing the Weapon Target Assignment (WTA) Problem, the problem of assigning weapons to targets while considering their effective probability of kill, began with Manne's seminal work in 1958. ... An improved genetic algorithm for target assignment, optimization of naval fleet air defense. The Sixth World Congress on Intelligent ...

  8. Diversity Improved Genetic Algorithm for Weapon Target Assignment

    Abstract. There are many optimization problems in military applications, among which the weapon target assignment (WTA) problem is the most typical and the most widely studied problem. Plenty of evolutionary algorithms-based methods are studied for resolving it. However, the quality of the solutions of WTA still has a lot of room for improvement.

  9. Immune Genetic Algorithm for Weapon-Target Assignment Problem

    An Immune Genetic Algorithm (IGA) is used to solve weapon-target assignment problem (WTA). The used immune system serves as a local search mechanism for genetic algorithm. Besides, in our implementation, a new crossover operator is proposed to preserve good information contained in the chromosome. A comparison of the proposed algorithm with several existing search approaches shows that the IGA ...

  10. Improved Genetic Algorithm for Weapon Target Assignment Problem

    Among them, genetic algorithm (GA) is the earliest and most mature optimization algorithm, and has been well applied in solving weapon target assignment (WTA) problem. In this paper, the implementation of GA is introduced. Aiming at the defect that traditional GA is easy to fall into local optimum, a fitness function control strategy based on ...

  11. Improved Assignment Model and Genetic Algorithm for Solving

    On this basis, the genetic algorithm is used to solve the problem of antiaircraft weapon-target optimal assignment. Aiming at the slow convergence rate of genetic algorithm(GA), the individual and group extremum updating in particle swarm optimization(PSO) is used as the best individual preserving strategy in genetic algorithm, so as to improve ...

  12. Weapon‐Target Assignment Problem by Multiobjective Evolutionary

    The weapon-target assignment (WTA) problem is a key issue in Command & Control (C2). Asset-based multiobjective static WTA (MOSWTA) problem is known as one of the notable issues of WTA. ... proposed a genetic algorithm (GA) with greedy eugenics for the target-based SWTA. Wang et al. proposed an improved target-based SWTA model and used the ant ...

  13. Genetic algorithm with domain knowledge for weapon-target assignment

    A Genetic Algorithm with Domain Knowledge for Weapon-Target Assignment Problems 295 Sandell, N. R., and LeBlanc, R., 1997, "A Decision Aid for Theater Missile Defense," Pro-

  14. The Robust Weapon Target Assignment Problem

    The JFS is known as the weapon target assignment problem (WTAP) in military operations research. Specifically, WTAP involves allocating a set of weapons, W = {1, 2, , W}, and muni- tions, M = {1, 2, , M}, to targets from a given set T = {1, 2, , T}, in order to minimize expected enemy threat. Each target t [ T is destroyed by weapon w [ W ...

  15. A new exact algorithm for the Weapon-Target Assignment problem

    1. Introduction. The Weapon-Target Assignment (WTA) problem is of military importance. In this problem, we have a set of m weapons, W, and a set of n targets, T; the objective is to find an optimal assignment of weapons to targets such that the expected total damage of the targets is maximized (or equivalently, the expected total survival possibility of the targets is minimized).

  16. A genetic algorithm with domain knowledge for weapon‐target assignment

    In this paper, a novel genetic algorithm, including domain specific knowledge into the crossover operator and the local search mechanism for solving weapon‐target assignment (WTA) problems is proposed. The WTA problem is a full assignment of weapons to hostile targets with the objective of minimizing the expected damage value to own‐force ...

  17. A heuristic genetic algorithm for solving constrained Weapon-Target

    The Weapon-Target Assignment (WTA) problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. Generic algorithm and heuristic algorithm are widely used for solving it but hardly be good enough considering the disadvantages of each. We firstly transform the nonlinear integer constrained WTA problem into a linear integer problem and suggest genetic ...

  18. Weapon-target assignment problem: exact and approximate solution algorithms

    The Weapon-Target Assignment (WTA) problem aims to assign a set of weapons to a number of assets (targets), such that the expected value of survived targets is minimized. The WTA problem is a nonlinear combinatorial optimization problem known to be NP-hard. This paper applies several existing techniques to linearize the WTA problem. One linearization technique (Camm et al. in Oper Res 50(6 ...

  19. String- and permutation-coded genetic algorithms for the static weapon

    In the Weapon-Target Assignment Problem, m enemy targets are inbound, each with a value V j representing the damage it may do. The defense has n weapons, and the probability that weapon i will kill target j is p ij.The problem is to assign the weapons to targets so as to reduce as much as possible the total expected value of the targets.

  20. PDF A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target

    The sensor-weapon-target assignment (S-WTA) problem, as one of the most important issues in C4ISR [1,2], has attracted great attention in recent years. Its objective is to find an appropriate

  21. The Weapon-Target Assignment Problem

    A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem. A novel genetic algorithm is proposed to improve the solution of this formulated S-WTA model, based on the prior knowledge of this problem, a problem-specific population initialization method and two novel repair operators.

  22. Immune Genetic Algorithm for Weapon-Target Assignment Problem

    A comparison of the proposed algorithm with several existing search approaches shows that the IGA outperforms its competitors on all tested WTA problems. An Immune Genetic Algorithm (IGA) is used to solve weapon-target assignment problem (WTA). The used immune system serves as a local search mechanism for genetic algorithm. Besides, in our implementation, a new crossover operator is proposed ...

  23. Exact and Heuristic Algorithms for the Weapon-Target Assignment Problem

    [email protected]. The weapon-target assignment (WTA) problem is a fundamental problem arising in defense-related applications of oper ations research. This problem consists of optimally assigning n weapons to m targets so that the total expected survival value of the targets after all the engagements is minimal.