Solving Weapon-Target Assignment Problem using Discrete Particle Swarm Optimization

This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which a priority set is constructed to control the local search and converge to the global optimum efficiently. Then the particles would be updated based on the information of priority set. Furthermore, the concept of "permutation" is employed to the update strategy. Finally, particles will be reinitialized as long as they are stagnated in the search space. The experimental results illustrate that the DPSO is a promising optimization method, which is especially useful for optimization problem with discrete variables

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