A Parallel Simulated Annealing Algorithm for Weapon-Target Assignment Problem

Sonuç, Emrullah; Sen, Baha; Bayir, Safak

doi:10.14569/ijacsa.2017.080412

Cited by 25 publications

(10 citation statements)

References 12 publications

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“…The results obtained by Sonuç et al using Simulated Annealing and Population-Based Simulated Annealing, in solving the weapon target assignment problem, were added to the study. SA, PSA, and SSA Algorithms have been compared and it has been proven that the SSA algorithm gives better results [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Solving Weapon-Target Assignment Problem with Salp Swarm Algorithm

Avcı

Yildirim

2023

Teh. vjesn.

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The weapon target problem is a combinatorial optimization problem. It aims to have the weapons on target properly assigned for the intended purposes. When focused on its target, it does things with its effective attack research in mind. It is an ongoing problem program to minimize survivors. This study, using the weapon target assignment model calculates the expected probabilities on the target with the salp model. The nature of this SHA model is designed to be appropriately predicted for this particular use. The Salp Swarm Algorithm (SSA) is a metaheuristic method of methods approaching the solution set as an approximation. Optimum solution or optimum example is in a working example. This study was done with 12 problem examples (200 training and 200 targets with pleasure to observe, to test the efficiency of SSA). In the problem, the iteration resulted in optimum results at the end of the definite usage time.

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Section: Literature Reviewmentioning

confidence: 99%

Solving Weapon-Target Assignment Problem with Salp Swarm Algorithm

Avcı

Yildirim

2023

Teh. vjesn.

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“…Then initialize these bits by different targets; 13: end if 14: Evaluate the objective functions of the i th individual according to equation 2; 15: end for Algorithm 2: Initialization. 6 Complexity closet neighbors. The mating restriction in this framework can make two solutions mate which are selected in two neighbors, respectively.…”

Section: Mating Restriction and The Neighboring Subpopulationsmentioning

confidence: 99%

“…Weapon-target assignment (WTA) problem is one of the most important problems in Command & Control (C 2 ) [1]. It has attracted a great attention in recent years [2][3][4][5][6]. The WTA problem can be considered as a kind of resource allocation problem [7].…”

Section: Introductionmentioning

confidence: 99%

Weapon‐Target Assignment Problem by Multiobjective Evolutionary Algorithm Based on Decomposition

Zhou

Pan

et al. 2018

Complexity

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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. Since this is an NP-complete problem, multiobjective evolutionary algorithms (MOEAs) can be used to solve it effectively. The multiobjective evolutionary algorithm based on decomposition (MOEA/D) is a practical and promising multiobjective optimization technique. However, MOEA/D is originally designed for continuous multiobjective optimization which loses its efficiency to discrete contexts. In this study, an improved MOEA/D is proposed to solve the asset-based MOSWTA problem. The defining characteristics of this problem are summarized and analyzed. According to these characteristics, an improved MOEA/D framework is introduced. A novel decomposition mechanism is designed. The mating restriction and selection operation are reformulated. Furthermore, a problem-specific population initialization method is presented to improve the efficiency of the proposed algorithm, and a novel nondominated solution-selection method is put forward to handle the constraints of Pareto front. Appropriate extensions of four MOEA variants are developed in comparison with the proposed algorithm on some generated scenarios. Extensive experiments demonstrate that the proposed method is effective and promising.

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“…Ayrıca, hibrit yöntemin üzerinde farklı seçim ve komşu-luk operatörleri uygulandıgında, en iyi sonuçların yer degiştirme operatörü ve rulet tekeri seçim operatörü kullanılarak elde edildigi gözlemlenmiş ve sunulmuştur. Hatta, bu makalede gösterilmemiş olsa da Sonuç ve arkadaşlarının geliştirdigi paralel TB yönteminden de daha iyi sonuçlar elde edilmiştir ( [24] makalesinde Tablo V deki degerlere bakılabilir).…”

Section: Tartışma Ve Sonuçunclassified

“…SHA problemi için önceki çalışmalar ile adil bir karşılaştırma saglanması amacıyla parametre degerleri, kolonide bulunan arı sayısı, limit deger ve maksimum iterasyon sayısı sırasıyla 50, 1000, 200.000 olarak belirlenmiştir. Algoritma 3 C programlama dilinde yazılarak Sonuç ve arkadaşları tarafından üretilmiş olan problem örnekleri [24] üzerinde, i7-3930K 3.2 GHz işlemciye sahip 32 GB bellegi bulunan makina üzerinde 10 kez çalıştırıldıgında Tablo 1'de bulunan sonuçlar elde edilmiştir. for i= 1 to BS do 7:…”

Section: Hesaplama Denemeleriunclassified

Silah Hedef Atama Problemi için Tavlama Benzetimli Bir Hibrit Yapay Arı Kolonisi Algoritması

Kutucu

Durgut²

2018

SDÜ Fen Bil Enst Der

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Anahtar KelimelerHedef silah atama, Yapay arı kolonisi, Tavlama benzetimi, Meta-sezgisel algoritmalar Özet: Bu çalışmada, sadece savunma alanında uygulamaları olmayıp iş dünyasında da uygulamaları olan çok zor kombinatoriyel optimizasyon problemlerinden statik silah hedef atama problemini ele alıyoruz. Silah hedef atama probleminin amacı, hedeflerin minimum toplam hayatta kalma degeri ile silahların hedeflere atanmasını bulmaktır. Silah hedef atama probleminin NP-tam problemi oldugu bilinmektedir. Bu makalede, silah hedef atama problemine etkili bir çözüm saglamak için tavlama benzetimi algoritması kullanarak hibrit bir yapay arı kolonisi algoritması önermekteyiz. Abstract: In this work, we consider the static weapon target assignment problem which is a very hard combinatorial optimization problem has not only defense-related applications but business world applications. The aim of the weapon target assignment problem is to find an assignment of weapons to targets with the minimum total survival value of the targets. The weapon target assignment problem is known to be NP-complete problem. In this paper, we propose a hybrid artificial bee colony algorithm with simulated annealing algorithm to give an efficient solution to the weapon target assignment problem. We tested the proposed algorithm with benchmark problem instances and compared it with some other meta-heuristics in the literature. Computational tests show that our algorithm is competitive and satisfactory.

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A Parallel Simulated Annealing Algorithm for Weapon-Target Assignment Problem

Cited by 25 publications

References 12 publications

Solving Weapon-Target Assignment Problem with Salp Swarm Algorithm

Solving Weapon-Target Assignment Problem with Salp Swarm Algorithm

Weapon‐Target Assignment Problem by Multiobjective Evolutionary Algorithm Based on Decomposition

Silah Hedef Atama Problemi için Tavlama Benzetimli Bir Hibrit Yapay Arı Kolonisi Algoritması

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