Solving TSP by an ACO-and-BOA-Based Hybrid Algorithm
Combined with the idea of the Bean Optimization algorithm (BOA), the ant colony optimization (ACO) algorithm is presented to solve the well known traveling salesman problem (TSP). The core of this algorithm is using BOA to optimize the control parameters of ACO which consist of heuristic factor, pheromone evaporation factor and random selection threshold, and applying ant colony system to solve two typical TSP. The new algorithm effectively overcomes the influence of control parameters of ACO and decreases the numbers of experiments. The novel hybrid algorithm ACOBOA finds the balance between exploiting the optimal solution and enlarging the search space. The results of the experiments show that ACOBOA has better optimization performance and efficiency than the general ant colony optimization algorithm and genetic algorithm. The new algorithm can also be generalized to solve other NP problems.
ant colony optimization bean optimization algorithm traveling salesman problem
Yunming Li
Nanjing College of Chemical Technology Nanjing, China
国际会议
太原
英文
189-192
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）