An Improved Nondominated Sorting Genetic Algorithm III Method for Solving Multiobjective Weapon-Target Assignment Part I: The Value of Fighter Combat

You, Li; Kou, Yingxin; Li, Zhanwu

doi:10.1155/2018/8302324

Cited by 20 publications

(14 citation statements)

References 62 publications

(94 reference statements)

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“…, b n , and n k�1 a k � n k�1 b k � const, and if the variance of the numbers b k is higher than that of a k , i.e., var(b k ) > var(a k ), then n k�1 b k < n k�1 a k . Similarly, we observe equations (13) and (14) and assume that there exists an optimal solution x * ij ∈ 0, 1 { }, ∀i, j for the linear summation (13); however, the solution x * ij ∈ 0, 1 { }, ∀i, j is not optimal for the objective function (14), namely,…”

Section: Maximum Consensus Technique Specifically Eachmentioning

confidence: 99%

“…Several centralized algorithms to solve WTA problems are proposed based on the research results of operations research and example include the heuristic algorithm [10], memetic algorithm [11], genetic algorithm [12,13], particle swarm optimization algorithm [14], bee colony algorithm [15], and game theoretic strategy [16]. A centralized algorithm efficiently obtains an optimal solution if the number of weapons and targets is low.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Algorithms for Weapon-Target Assignment in Swarming Combat System

Zhao

Wang

Kong

2019

Mathematical Problems in Engineering

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Swarming small unmanned aerial or ground vehicles (UAVs or UGVs) have attracted the attention of worldwide military powers as weapons, and the weapon-target assignment (WTA) problem is extremely significant for swarming combat. The problem involves assigning weapons to targets in a decentralized manner such that the total damage effect of targets is maximized while considering the nonlinear cumulative damage effect. Two improved optimization algorithms are presented in the study. One is the redesigned auction-based algorithm in which the bidding rules are properly modified such that the auction-based algorithm is applied for the first time to solve a nonlinear WTA problem. The other one is the improved task swap algorithm that eliminates the restriction in which the weights of the edges on graph G must be positive. Computational results for up to 120 weapons and 110 targets indicate that the redesigned auction-based algorithm yields an average improvement of 37% over the conventional auction-based algorithm in terms of solution quality while the additional running time is negligible. The improved task swap algorithm and the other two popular task swap algorithms almost achieve the same optimal value, while the average time-savings of the proposed algorithm correspond to 53% and 74% when compared to the other two popular task swap algorithms. Furthermore, the hybrid algorithm that combines the above two improved algorithms is examined. Simulations indicate that the hybrid algorithm exhibits superiority in terms of solution quality and time consumption over separately implementing the aforementioned two improved algorithms.

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Section: Maximum Consensus Technique Specifically Eachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decentralized Algorithms for Weapon-Target Assignment in Swarming Combat System

Zhao

Wang

Kong

2019

Mathematical Problems in Engineering

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“…These three traditional tools are all used to perform multi-directional and global searches to explore the set of Pareto solutions. This is usually done with two or more objective functions and a number of constraints (Li et al, 2018;Liu et al, forthcoming). Classic OR algorithms may require more knowledge than we actually have, in which case these AI tools provide for something like an 'automated heuristic'.…”

Section: An Ai Data Mining Toolboxmentioning

confidence: 99%

Open Source Foundations for Spatial Decision Support Systems

Albrecht¹

2018

giforum

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Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools have been developed by open source communities. In stark contrast to the abundance of OpenGeo software, there is a dearth of open source SDSS. The core of the article is a discussion of different approaches that lend themselves as platforms to develop an open source framework to build a variety of SDSS.

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“…Li et al [14] designed the objectives maximizing the total effectiveness of attack and minimize the cost of missiles. In [15], Li, You, et al added the residual weapons into previous work [14] to establish an MWTA formulation with three objectives. Volle and Rogers [16] presented the MWTA problem optimizing the operational effectiveness and the relative timing of agents' arrival.…”

Section: Introductionmentioning

confidence: 99%

Constrained Multi-Objective Weapon Target Assignment for Area Targets by Efficient Evolutionary Algorithm

et al. 2019

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The weapon target assignment (WTA) problem is the crucial decision support in Command & Control (C2). In the classic WTA model, the point-to-point saturation salvo has a low efficiency-cost ratio when the swarming targets, which have the advantage of low casualty, low cost and recyclable, become the major operational units. The constraint is less studied for the operational intention of the decision-maker. In this paper, a constrained multi-objective weapon target assignment (CMWTA) model is formulated for area targets. The optimization objectives are minimizing collateral damage and resource consumption. The multi-constraint is derived from the actual operational requirements of security evasion, damage threshold, and preference assignment. To solve CMWTA efficiently, a novel multi-objective optimization evolutionary algorithm (MOEA) is proposed to obtain the non-dominated solutions as the alternative plans for the decision-maker. A self-adaptive sorting algorithm is proposed to guarantee the completeness of the Paretooptimal set, and a cooperative evolutionary mechanism is adopted to strengthen the convergence. For handling multi-constraint, a repair mechanism is proposed to improve the quality of infeasible solutions, and the measurement of constraint violation is designed to evaluate the infeasible solutions. A variant of the convergence metric is introduced to evaluate the algorithms solving multi-objective weapon target assignment (MWTA) problem. The experimental results show the effectiveness and superiority of the proposed approaches.INDEX TERMS Constrained weapon target assignment, collateral damage, multi-objective optimization algorithm, decision support system.

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An Improved Nondominated Sorting Genetic Algorithm III Method for Solving Multiobjective Weapon-Target Assignment Part I: The Value of Fighter Combat

Cited by 20 publications

References 62 publications

Decentralized Algorithms for Weapon-Target Assignment in Swarming Combat System

Decentralized Algorithms for Weapon-Target Assignment in Swarming Combat System

Open Source Foundations for Spatial Decision Support Systems

Constrained Multi-Objective Weapon Target Assignment for Area Targets by Efficient Evolutionary Algorithm

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