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A non-dominated sorting genetic algorithm for a bi-objective pick-up and delivery problem

Abstract : Some companies must transport their personnel within facilities. This is especially the case for oil companies that use helicopters to transport engineers, technicians and assistant personnel from platform to platform. This operation has the potential to become expensive if the transportation routes are not correctly planned and provide a bad quality of service. Here this issue is modelled as a pick-up and delivery problem where a set of transportation requests should be scheduled in routes, minimizing the total transportation cost while the most urgent requests are satisfied by priority. To solve the problem, a method based on a Non-dominated Sorting Genetic Algorithm (NSGA-II) is proposed. This algorithm is tested on both randomly generated and real instances provided by a petroleum company. The results show that the proposed algorithm improves the best-known solutions.
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https://hal-utt.archives-ouvertes.fr/hal-02478682
Contributor : Daniel Gavrysiak <>
Submitted on : Friday, February 14, 2020 - 9:33:07 AM
Last modification on : Wednesday, July 22, 2020 - 9:14:03 AM

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Nubia Velasco, Pierre Dejax, Christelle Guéret, Christian Prins. A non-dominated sorting genetic algorithm for a bi-objective pick-up and delivery problem. Engineering Optimization, Taylor & Francis, 2012, 44 (3), pp.305-325. ⟨10.1080/0305215X.2011.639368⟩. ⟨hal-02478682⟩

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