Ant colony optimization with memory-based immigrants for the dynamic vehicle routing problem - Mavrovouniotis, Michalis; Yang, Shengxiang (My University, 2012)
A recent integration showed that ant colony optimization (ACO) algorithms with immigrants schemes perform well on different variations of the dynamic travelling salesman problem. In this paper, we address ACO for the dynamic vehicle routing problem (DVRP) with traffic factor where the changes occur in a cyclic pattern. In other words, previous environments will re-appear in the future. Memory-based immigrants are used with ACO in order to collect the best solutions from the environments and use them to generate diversity and transfer knowledge when a dynamic change occurs. The results show that the proposed algorithm, with an appropriate size of memory and immigrant replacement rate, outperforms other peer ACO algorithms on different DVRP test cases. © 2012 IEEE.
Keywords: Evolutionary algorithms; Traveling salesman problem; ACO algorithms; Ant Colony Optimization (ACO); Ant Colony Optimization algorithms; Cyclic patterns; Dynamic changes; Dynamic vehicle routing problems; Replacement rates; Test case; Traffic factors; Travelling salesman problem; Artificial intelligence