Improved local search based modified ABC algorithm for TSP problem
作者： Neha Pathak , Manuj Mishra , Shiv Pratap Singh Kushwah
关键词: Local search (optimization) 、 Difference-map algorithm 、 Genetic algorithm 、 Algorithm 、 Population-based incremental learning 、 Algorithm design 、 Mathematics 、 Mathematical optimization 、 Swarm intelligence 、 FSA-Red Algorithm 、 Local optimum
摘要: Swarm intelligence systems are basically made up simple agent's populations which interacting locally with each other and their surroundings. These agents local interaction can be negative, positive or neutral. Here helps to solve a problem while negative block the for solving problem. swarm's performance does not affected by neutral interaction. This work proposed incremental enhanced ABC algorithm search is used reducing without complexifying behavior. in algorithm, after scout bee phase, one supplementary phase form of mutation operator, part genetic used. With use this an may stopped into optima because changing best position. The experimental outcomes show that efficiency algorithm. Finally compared novel ABCM (artificial colony mutation)
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