Multi-objective open location-routing model for relief distribution networks with split delivery and multi-mode transportation under uncertainty

Abstract

In this study, the response phase of the management of natural disasters is investigated. One of the important issues in this phase is determining the distribution areas and timely distribution of relief to affected areas in which transportation routing is of a critical matter. In the event of disasters, especially flood and earthquake, terrestrial transportation is not that much easy due to the damage to many infrastructures. For this reason, we propose that delivering relief from the distribution areas to disaster stricken places should be done simultaneously by terrestrial as well as aerial transportation modes to increase route reliability and reduce travel time. In this study, for relief allocation after earthquake, we offer a mixed-integer nonlinear open location-routing model in uncertainty condition. This model includes several contradictory objectives and variety of factors such as travel time, total costs, and reliability. In order to solve this model, a hybrid solution by combining robust optimization and fuzzy multiobjective programming has been used. The performance and effectiveness of the offered model and solution approach has been investigated through a case study on the earthquake in East Azerbaijan, Iran. Our computational results show the solution we have offered for real problems has been effective.

Location‐routing problem: a classification of recent research

“…As shown in Table 6, the application of LRP models to optimize a case of waste management network planning (e.g., Rahim and Sepil, 2014;Sheriff et al 2014;Asefi et al, 2019;Hu et al, 2019) is by far the most popular study. Other popular application areas are emergency and disaster management (Rath and Gutjahr, 2014;Wang et al, 2014;Bozorgi-Amiri and Khorsi, 2016;Xu et al, 2016;Burkart et al, 2017;Veysmoradi et al, 2018;Wu et al, 2018;Liu et al, 2019a;Xiong et al, 2019), food distribution network planning (Solak et al, 2014;Hemmelmayr et al, 2017;Wu et al, 2017;Validi et al, 2018;Wang et al, 2018bWang et al, , 2018cChao et al, 2019;Saragih et al, 2019), and city logistics (Zhou et al, 2016; Zhou et al, 2017;Wang et al, 2018b;Chao et al, 2019;Rodriguez et al, 2019;Saragih et al, 2019;Schmidt et al, 2019). Each of these areas presents unique challenges for the researchers in the efforts to develop a model that correctly represents the real-life situation.…”

“…Meanwhile, 5.86% works deal with the case when customer nodes require either delivery or pickup services (e.g., Sun, 2015;Dukkanci and Kara, 2017;Mousavi and Vahdani, 2017). Numerous works have incorporated the presence of time window constraints in their models, either in the form of soft time window constraints (e.g., Rabbani et al, 2018a;Veysmoradi et al, 2018;Wang et al, 2018bWang et al, , 2018cHu et al, 2019) as found in 6.31% works, or hard time window constraints (e.g., Ceselli et al, 2014;Koç et al, 2016a;Basirati et al, 2019;Capelle et al, 2019;Koç et al, 2019) as indicated in 16.67% works. The presence of time windows in LRP is proven to be a realistic attribute that should be considered by the decision maker in several time-sensitive domain areas, such as agriculture (Akararungruangkul and Kaewman, 2018), food distribution (Wu et al, 2017), disaster relief distribution, (Liu et al, 2019a), and healthcare logistics (Ceselli et al, 2014).…”

Pre-Positioning of a Relief Chain in Humanitarian Logistics Under Uncertainty in Road Accidents: A Real-Case Study

“…Finally, two multi-objective meta-heuristic algorithms were proposed to obtain a near-optimal solution. Veysmoradi, Vahdani, Sartangi and Mousavi [23] investigated the response phase in the management of natural disasters, and offered a mixed-integer nonlinear open location-routing model in conditions of uncertainty.…”

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

“…Location, allocation, routing and inventory decisions are regarded in various types of SC problems [3,4,5]. Lot sizing is regarded in some studies of CLSC besides the other strategic and tactical decisions of the system.…”