Uncertain multiobjective traveling salesman problem

Zutong Wang, Jiansheng Guo, Mingfa Zheng and Ying Wang

European Journal of Operational Research, 2015, vol. 241, issue 2, 478-489

Abstract: Traveling salesman problem is a fundamental combinatorial optimization model studied in the operations research community for nearly half a century, yet there is surprisingly little literature that addresses uncertainty and multiple objectives in it. A novel TSP variation, called uncertain multiobjective TSP (UMTSP) with uncertain variables on the arc, is proposed in this paper on the basis of uncertainty theory, and a new solution approach named uncertain approach is applied to obtain Pareto efficient route in UMTSP. Considering the uncertain and combinatorial nature of UMTSP, a new ABC algorithm inserted with reverse operator, crossover operator and mutation operator is designed to this problem, which outperforms other algorithms through the performance comparison on three benchmark TSPs. Finally, a new benchmark UMTSP case study is presented to illustrate the construction and solution of UMTSP, which shows that the optimal route in deterministic TSP can be a poor route in UMTSP.

Keywords: Uncertainty modeling; Traveling salesman problem; Multiobjective optimization; Artificial bee colony algorithm (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:241:y:2015:i:2:p:478-489

DOI: 10.1016/j.ejor.2014.09.012

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