HighlightsThe single-vehicle static repositioning problem is studied.An enhanced chemical reaction optimization (CRO) is proposed to solve the problem.The enhanced CRO incorporates two new neighbor-node sets and intensive search.The results show that the enhanced CRO gives better solution than the original CRO.The enhanced CRO could provide high quality solutions using short computing times.

    AbstractIn this paper, the single-vehicle static repositioning problem is studied. The objective of repositioning is to minimize the weighted sum of unmet customer demand and operational time on the vehicle route. To solve this problem, chemical reaction optimization (CRO) is proposed to handle the vehicle routes, and a subroutine is proposed to determine the loading and unloading quantities at each visited station. An enhanced version of CRO is proposed to improve the solution quality of the original CRO by adding new operators, rules, and intensive neighbor solution search methods. The concept of a neighbor-node set is proposed to narrow the solution search space. To illustrate the efficiency and accuracy of the enhanced CRO, different test scenarios are set and the results obtained from IBM ILOG CPLEX, the original CRO, and the enhanced CRO are compared. The computational results indicate that the enhanced CRO provides high-quality solutions with shorter computing times than those of IBM ILOG CPLEX and provides better solutions than the original CRO. The results also demonstrate that incorporation of the two neighbor-node sets into the enhanced CRO improves the solution quality, and the probability of running the intensive search should increase with iteration in the final part of the main stage of the algorithm to obtain better solutions.


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    Title :

    Chemical reaction optimization for solving a static bike repositioning problem


    Contributors:
    Szeto, W.Y. (author) / Liu, Ying (author) / Ho, Sin C. (author)


    Publication date :

    2016-01-01


    Size :

    32 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English