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Local search for the undirected capacitated arc routing problem with profits

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  • Zachariadis, E.E.
  • Kiranoudis, C.T.

Abstract

This paper deals with a recently introduced routing problem variant called the undirected capacitated arc routing problem with profits (UCARPP). The UCARPP model considered in the present study is primarily aimed at generating the route set which maximizes the profit collected from a set of potential customers, represented by edges of the examined transportation network. The secondary objective is to minimize the total route travel time. The generated routes are subject both to capacity and travel time constraints. To tackle the examined problem, we propose a local search metaheuristic development which explores two solution neighborhood structures. The conducted search is effectively diversified by means of the promises concept which is based on the aspiration criteria used in tabu search approaches. The proposed algorithm was tested on UCARPP benchmark instances taken from the literature. It efficiently produced high-quality results, improving several previously best known solutions.

Suggested Citation

  • Zachariadis, E.E. & Kiranoudis, C.T., 2011. "Local search for the undirected capacitated arc routing problem with profits," European Journal of Operational Research, Elsevier, vol. 210(2), pages 358-367, April.
    • Handle: RePEc:eee:ejores:v:210:y:2011:i:2:p:358-367
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    References listed on IDEAS

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    1. Vansteenwegen, Pieter & Souffriau, Wouter & Berghe, Greet Vanden & Oudheusden, Dirk Van, 2009. "A guided local search metaheuristic for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 118-127, July.
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    7. Dominique Feillet & Pierre Dejax & Michel Gendreau, 2005. "The Profitable Arc Tour Problem: Solution with a Branch-and-Price Algorithm," Transportation Science, INFORMS, vol. 39(4), pages 539-552, November.
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    Cited by:

    1. Ávila, Thais & Corberán, Ángel & Plana, Isaac & Sanchis, José M., 2016. "A branch-and-cut algorithm for the profitable windy rural postman problem," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1092-1101.
    2. Archetti, Claudia & Corberán, Ángel & Plana, Isaac & Sanchis, José Maria & Speranza, M. Grazia, 2015. "A matheuristic for the Team Orienteering Arc Routing Problem," European Journal of Operational Research, Elsevier, vol. 245(2), pages 392-401.
    3. Ding, Honglin & Li, Jianping & Lih, Ko-Wei, 2014. "Approximation algorithms for solving the constrained arc routing problem in mixed graphs," European Journal of Operational Research, Elsevier, vol. 239(1), pages 80-88.
    4. Dontas, Michael & Sideris, Georgios & Manousakis, Eleftherios G. & Zachariadis, Emmanouil E., 2023. "An adaptive memory matheuristic for the set orienteering problem," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1010-1023.
    5. Afsaneh Amiri & Majid Salari, 2019. "Time-constrained maximal covering routing problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 415-468, June.
    6. Enrique Benavent & Ángel Corberán & Luís Gouveia & Maria Mourão & Leonor Pinto, 2015. "Profitable mixed capacitated arc routing and related problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 244-274, April.

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