Parallel Ant Colonies with Heuristics Applied to Weapon-Target Assignment Problems
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In this paper, an algorithm of parallel ant colonies with heuristics applied to Weapon-Target Assignment (WTA) problems is proposed. WTA problems, known as NP-complete problems, are to find the proper assignment of weapons to targets with the objective of minimizing the expected damage value of own-force assets. Basically, the proposed algorithm is a parallel mechanism based on ant colony optimization (ACO) and has cooperative interactions among ant colonies. It has both the advantage of ACO, the ability to find feasible solutions and to avoid premature convergence, and the advantage of heuristics, the ability to conduct fine-tuning to find better solutions. In this paper, several WTA cases are tested to prove the superiority of our algorithm. Simulation results are also reported and the proposed algorithm indeed has admirable performances in all cases.
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