Abstract
The Weapon-Target Assignment (WTA) problem is one of the most important optimization problems in military operation research. In the WTA problem, assets of defense aim the best assignment of each weapon to target for decreasing expected damage directed by the offense. In this paper, Modified Crow Search Algorithm (MCSA) is proposed to solve the WTA problem. In MCSA, a trial mechanism is used to improve the quality of solutions using parameter LIMIT. If the solution is not improved after a predetermined number of iterations, then MCSA starts with a new position in the search space. Experimental results on the different sizes of the WTA problem instances show that MCSA outperforms CSA in all problem instances. Also, MCSA achieved better results for 11 out of 12 problem instances compared with four state-of-the-art algorithms. The source codes of MCSA for the WTA are publicly available at http://www.3mrullah.com/MCSA.html.
Highlights
Weapon-Target Assignment (WTA) problem is one of the most important optimization problems in military operation research
This paper aims to improve the quality of solutions for the static weapon-target assignment problem (SWTA) problem using a modified crow search algorithm (MCSA)
The results show that Modified Crow Search Algorithm (MCSA) outperforms Crow Search Algorithm (CSA) in all problem instances
Summary
Weapon-Target Assignment (WTA) problem is one of the most important optimization problems in military operation research. The main difference between the SWTA and the DWTA is the timing of launching weapons to targets. In the WTA problem, the aim is to minimize the damage caused by attacks of the targets. Several exact and approximation algorithms [2,3,4] have recently involved in solving the WTA problem. Since the WTA is an NP-complete problem [5], exact algorithms can not solve large-scale WTA problems in polynomial time. To overcome this problem, metaheuristic algorithms are presented to solve the WTA problem. Metaheuristic algorithms provide a valid solution in a reasonable time [6]
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