Affiliations: School of Computer Science, Wuhan University of Science and Technology, Wuhan 420081, P.R. China. [email protected] | Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430081, P.R. China. [email protected]
Note: [] Address for correspondence: Hubei Province Key Laboratory of Intelligent Information Processing, and Real-time Industrial System, Wuhan 430081, P.R. China
Abstract: The multiobjective multiple traveling salesman problem (MmTSP), in which multiple salesmen and objectives are involved in a route, is known to be NP-hard. The MmTSP is more appropriate for real-life applications than the classical traveling salesman problem (TSP), however it has not received the same amount of attention. Due to the high complexity of the MmTSP, a promising algorithm for solving it must be based on a global search procedure. This paper proposes a hybrid global search algorithm, that belongs to the membrane computing framework. The search behavior of the algorithm is enhanced by a communication mechanism. The multichromosome representation is considered to reduce the excess runtime. The effectiveness of the proposed algorithm is tested on the MmTSP with disparately-scaled objective functions, salesmen and problem sizes. The experimental results are compared with the NSGA-II and several evolutionary strategies with decomposition, including simulated annealing algorithm, hill climbing method, pure evolutionary algorithm, and genetic algorithm.
