Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty

Vahdani, Behnam; Veysmoradi, D.; Noori, F.; Mansour, F A

doi:10.1016/j.ijdrr.2017.10.015

Cited by 106 publications

(54 citation statements)

References 17 publications

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“…To make the model realistic, the authors considered some uncertainties and, to handle the uncertainties, a robust optimization approach was utilized and, finally, the ɛ-constraint method was used to solve the model. Another multi-objective robust optimization model was proposed by Vahdani, B., Veysmoradi, D., Noori, F., and Mansour, F. [94]. Between the two phases of their proposed model, in the first phase, the establishment of the distribution center and warehouse, as well as the storing of relief goods, was considered and, in the second phase, the distribution of relief goods to the affected areas was considered.…”

Section: Robust Optimization and Othersmentioning

confidence: 99%

A Systematic Literature Review on Mathematical Models of Humanitarian Logistics

Hezam

Nayeem

2020

Symmetry

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Humanitarian logistics (HL) is considered one of the most significant issues of disaster operations and management. Thus, HL operation should be viable enough to function well under the uncertain and complex nature of the disaster. Many difficulties in pre-and post-disaster phases bring both human and economic losses. Therefore, it is essential to make sure that the HL operations are designed efficiently. In the last two decades, several publications have emphasized efficient HL operations and proposed several mathematical models and algorithms to increase the efficiency of HL operations and motivated the necessity of a systematic literature review. A systematic literature review is deemed pertinent due to its transparent and detailed article searching procedure. In this study, due to the importance of the mathematical optimization model, we reviewed more than one hundred articles published between 2000 and 2020 to investigate the optimization models in the field of HL. We classified the optimization models into three main problems: facility location problems, relief distribution, and mass evacuation where each of the classified areas includes both deterministic and non-deterministic models.

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Section: Robust Optimization and Othersmentioning

confidence: 99%

A Systematic Literature Review on Mathematical Models of Humanitarian Logistics

Hezam

Nayeem

2020

Symmetry

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“…The larger scale of the problem is solved by the NSGA-II as well as the Reference Point Based NSGA-II (RPBNSGA-II), where they outperformed each other for the case of smaller instance and larger instance, respectively. The LIRP to supply multi-commodity to disaster sites is addressed in [81] while using two proposed models. The former model is based on the the assumption where one affected area only needs to be served by one distribution centre, while the latter deals the problem with the flexibility of split delivery allowing for more than one distribution centre to serve one affected site.…”

Section: Metaheuristics In Supply and Delivery Vrpsmentioning

confidence: 99%

“…In general, the modelling of classified VRPs in this survey can be divided by those adopting graph theory (such as the minimum cost flow model and spanning tree model), agent based model, such as in [113,119,124], among others, the set partitioning model, as can be seen in [51], and the MDP model. There is also a trend of the combined OR problem that also addressed the VRP to fully capture the important mechanism of humanitarian operations, such as the LRP, which can be seen in [42,44,48,73,74,77,79,89,138,139], followed by the LIRP in [80,81], scheduling and routing in [85,92], ARP in [96], as well as ALRP in [57].…”

Section: Current Trendsmentioning

confidence: 99%

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

et al. 2021

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The growing field of humanitarian operations is driven by frequent events of disasters seen in the world today. Within this field, Operations Research (OR) plays a critical role in alleviating the suffering of victims that are impacted by disasters. This paper focuses on the branch of a well-known OR problem, known as the Vehicle Routing Problem (VRP), within the selected scope of humanitarian operations. A total of 123 papers of the last decade are reviewed and classified under the humanitarian operations of supply and delivery, evacuation as well as rescue operations. Besides specific disaster management phases and disaster types, various modelling challenges are highlighted, hinting towards a richer and more complex VRP seen under selected model characteristic classifications. Furthermore, established solution approaches, including hybrid solutions, are highlighted and classified, discussing how they are applied in the context of these humanitarian operations. The inclusion of a machine learning solution approach under the same classification is proposed. Finally, the trend and future outlook of VRP for the suggested humanitarian operations are discussed and highlighted.

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“…Subsequently, they developed two meta-algorithms to solve their proposed problem. Moreover, Vahdani et al [29] developed a two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. Their goal was to minimize total cost and travel time and increase the reliability of relief routes.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective robust mathematical modeling for emergency relief in disaster under uncertainty

et al. 2020

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This paper presents a robust location-allocation planning problem for emergency relief in a disaster situation, which is formulated as a robust optimization model. It is a multi-objective, multi-commodity, multi-vehicle and multi-level logistics model considering injury variety through service prioritizing for more injuries and considering unmet demand of particular item type in various damaged areas, public donation of different relief goods, using capacitated medical centers and emergency centers regarding damage type and capacitated relief distribution centers and disaster management centers. This a non-linear mixed-integer programming model that simultaneously optimizes three objectives; i.e., maximizing service fairness to damaged areas, maximizing fair commodity disaster management, and minimizing the total logistics cost. To solve such a hard problem, a non-dominated sorting genetic algorithm (NSGA-II) is developed and the Taguchi method is applied to adjust its parameters. The ε-constraint method is used for the evaluation of the proposed algorithm performance. For more accurate validation, three comparison metrics, including diversification, spacing and mean ideal distance, are used. The results verify the algorithm's effectiveness in a reasonable computational time. Eventually, to examine the applicability of the presented model and the proposed algorithm, a case study is analyzed in the area located in the north of Iran, known with historical earthquake records and aggregated active faults.

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Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty

Cited by 106 publications

References 17 publications

A Systematic Literature Review on Mathematical Models of Humanitarian Logistics

A Systematic Literature Review on Mathematical Models of Humanitarian Logistics

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

Multi-objective robust mathematical modeling for emergency relief in disaster under uncertainty

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