2005Journal of Air Force Engineering UniversityRequires access

An Optimized Method for Assigning Targets Based on GA with Tabu Operator

Cheng Li

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Abstract

A mixed genetic algorithm with the tabu search operator is proposed for multi-channel optimized target - assigning in operation of air defense. Both the advantages of tabu search algorithm and those of genetic algorithm are integrated into this algorithm. This algorithm avoids the shortage of global search capability of the tabu search algorithm, improves the mountain climbing capability of the genetic algorithm, solves the problem of being easily immersed in local optimization in the genetic algorithm and enables the search course to have a memory capability. The simulation result shows that the algorithm can effectively give a satisfied solution to the problem in solving multi-channel optimized target - assignment.

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What this paper is about

A mixed genetic algorithm with the tabu search operator is proposed for multi-channel optimized target - assigning in operation of air defense. Both the advantages of tabu search algorithm and those of genetic algorithm are integrated into this algorithm. This algorithm avoids the shortage of global search capability of the tabu search algorithm, improves the mountain climbing capability of the genetic algorithm, solves the problem of being easily immersed in local optimization in the genetic algorithm and enables the search course to have a memory capability. The simulation result shows that the algorithm can effectively give a satisfied solution to the problem in solving multi-channel optimized target - assignment.

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Available abstract

A mixed genetic algorithm with the tabu search operator is proposed for multi-channel optimized target - assigning in operation of air defense. Both the advantages of tabu search algorithm and those of genetic algorithm are integrated into this algorithm. This algorithm avoids the shortage of global search capability of the tabu search algorithm, improves the mountain climbing capability of the genetic algorithm, solves the problem of being easily immersed in local optimization in the genetic algorithm and enables the search course to have a memory capability. The simulation result shows that the algorithm can effectively give a satisfied solution to the problem in solving multi-channel optimized target - assignment.

Key concepts: Tabu search, Hill climbing, Guided Local Search, Genetic algorithm, Mathematical optimization, Algorithm, Population-based incremental learning, Computer science

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