Literature DB >> 33405116

Multiobjective location-routing problem of relief commodities with reliability.

Hossein Beiki1, Seyed M Seyedhosseini2, Leonardus W W Mihardjo3, Seyed M Seyedaliakbar1.   

Abstract

The applicability and efficiency of location-routing problems for relief commodities motivate several researchers to develop optimization models and algorithms with regards to real-world cases. This study by presenting a multiobjective mixed integer mathematical model for the location-routing of the medical relief problem at the time of a disaster, proposes a new extension to this applicable model with reliability considerations. The proposed model focuses on the location of temporary relief centers and delivers the pharmaceutical commodities to centers at the shortest possible time with reliability assurance. The model includes three simultaneous objectives of minimizing response time, minimizing operational costs, and maximizing the reliability of the transportation network. As far as we know, this study firstly optimizes these three objectives simultaneously. Another novelty is to add the uncertainty of the problem. In this regard, the inherent uncertainty is formulated by a scenario-based approach. Considering the multiobjectiveness of the proposed model, the Epsilon constraint method as a solution algorithm has been used to solve the model. Results are tested for numerical examples via different scenarios. The results represent the excellent performance of the model to minimize the costs and to increase the reliability for the proposed location-routing problem of relief commodities.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

Entities:  

Keywords:  Mixed integer programming; Reliability; Relief commodity; Scenario-based approach

Year:  2021        PMID: 33405116     DOI: 10.1007/s11356-020-11891-w

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   5.190


  1 in total

1.  Sustainable supply chain network design.

Authors:  Amir M Fathollahi-Fard; Maxim A Dulebenets; Guangdong Tian; Mostafa Hajiaghaei-Keshteli
Journal:  Environ Sci Pollut Res Int       Date:  2022-02-03       Impact factor: 4.223

  1 in total

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