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Diversified local search strategy under scatter search framework for the probabilistic traveling salesman problem

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  • Liu, Yu-Hsin

Abstract

This paper focuses on introducing a concept of diversified local search strategy under the scatter search framework for the probabilistic traveling salesman problem (PTSP). Different combinations of three commonly used local search methods in the PTSP, i.e., 1-shift, 2-opt, and 3-opt, were used to investigate its effects. A set of numerical experiments were conducted to test the validity of the proposed strategy based on randomly generated test instances. The numerical results and the permutation test showed that the diversified local search strategy, especially by combining 1-shift and 2-opt algorithms, can most effectively solve the homogeneous and heterogeneous PTSP in most of the tested instances in comparison with the single local search strategy under scatter search framework.

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  • Liu, Yu-Hsin, 2008. "Diversified local search strategy under scatter search framework for the probabilistic traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 191(2), pages 332-346, December.
    • Handle: RePEc:eee:ejores:v:191:y:2008:i:2:p:332-346
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    Cited by:

    1. Liu, Yu-Hsin, 2011. "Incorporating scatter search and threshold accepting in finding maximum likelihood estimates for the multinomial probit model," European Journal of Operational Research, Elsevier, vol. 211(1), pages 130-138, May.
    2. Kang, Seungmo & Ouyang, Yanfeng, 2011. "The traveling purchaser problem with stochastic prices: Exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 209(3), pages 265-272, March.

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