Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics

Abstract

A general weapon-target assignment (WTA) problem is to find a proper assignment of weapons to targets with the objective of minimizing the expected damage of own-force asset. Genetic algorithms (GAs) are widely used for solving complicated optimization problems, such as WTA problems. In this paper, a novel GA with greedy eugenics is proposed. Eugenics is a process of improving the quality of offspring. The proposed algorithm is to enhance the performance of GAs by introducing a greedy reformation scheme so as to have locally optimal offspring. This algorithm is successfully applied to general WTA problems. From our simulations for those tested problems, the proposed algorithm has the best performance when compared to other existing search algorithms.

Security impact assessment of industrial automation systems using genetic algorithm and simulation

“…Weapon target pairing is an approach that assumes knowledge of killing probabilities for combinations of weapons and targets. Due to the complexity of the possible combinations and targets, effective algorithms for pairing several weapons and targets have emerged through the application of GA [27]. A GA for finding an optimal defense strategy for a complex system incorporating fault tolerant designs such as separation and redundancy is described by Levitin [28].…”

A Novel Genetic Algorithm for the Synthetical Sensor-Weapon-Target Assignment Problem

“…This problem is a constrained combinatorial optimization problem, which can be regarded as a nondeterministic polynomial time complete (NP-complete) problem [3]. For certain cases, S-WTA can be considered as a composite of two independent parts, i.e., the sensor-target assignment (STA) [4][5][6][7][8] and the weapon-target assignment (WTA) [9][10][11][12][13][14][15][16]. As the sensor is mainly used to obtain the information of the battlefield situation, the STA is performed in the mission of reconnaissance and surveillance to make decisions for the sensor management.…”

“…Among these algorithms, GA is one of the most important algorithms. Because GA has a simple framework, high flexibility, and strong convergence ability, it has been successfully applied in many real-world problems [35][36][37], especially in the WTA problem [13,23,38]. For these reasons, we believe that choosing GA to solve the S-WTA problem is reasonable and promising.…”

Effect-based weapon-target assignment optimization with collateral damage under control

“…It is well known that the assignment of weapons to targets alone is NP-complete [15]. Hence, most previous work in literature has been focused on the heuristic-based approach to solve EWTA (e.g., [3,6,11,13,14]) as opposed to the exact algorithm whose various flavors can be found in [1,5,7], and [17]. For the same reason, our Opt Controlled represents a heuristic algorithm based on the combinatorial auctions [9,10,16].…”