Multiobjective Location Routing Problem considering Uncertain Data after Disasters

Abstract

The relief distributions after large disasters play an important role for rescue works. After disasters there is a high degree of uncertainty, such as the demands of disaster points and the damage of paths. The demands of affected points and the velocities between two points on the paths are uncertain in this article, and the robust optimization method is applied to deal with the uncertain parameters. This paper proposes a nonlinear location routing problem with half-time windows and with three objectives. The affected points can be visited more than one time. The goals are the total costs of the transportation, the satisfaction rates of disaster nodes, and the path transport capacities which are denoted by vehicle velocities. Finally, the genetic algorithm is applied to solve a number of numerical examples, and the results show that the genetic algorithm is very stable and effective for this problem.

Location‐routing problem: a classification of recent research

“…It is shown that most of the recently proposed LRP models are still considering only deterministic data (76.58%). However, SLRP (e.g., Bertazzi and Maggioni, 2017;Chang et al, 2017;Saragih et al, 2019) and FLRP (e.g. Ghezavati and Morakabatchian, 2015;Zhalechian et al, 2016;Pekel and Kara, 2019) have started to receive more recognition with the presence of 5.86% and 15.32% from the total publications.…”

“…Only five articles have addressed the plan (Bertazzi and Maggioni, 2015;Tokgöz et al, 2015;Farrokhi-Asl et al, 2017;Tokgöz and Trafalis, 2017;Ghaffarinasab et al, 2018), while one work deals with the case where facilities can be positioned in any vertex and arc of a graph (Averbakh and Yu, 2018). The LARP also receives a little attention, with only 10 works (4.52%) found within the considered timeframe (Lopes et al, 2014;Riquelme-Rodríguez et al, 2016;Chang et al, 2017;Boccia et al, 2018;Çetinkaya et al, 2018;Chen et al, 2018;Cui et al, 2018;Amini et al, 2019;Fernández et al, 2019;Lu et al, 2019a).…”

A hybrid algorithm Tabu Search – GRASP for wounded evacuation in disaster response

“…Chang et al [22] studied the impact of large disasters on roads safety and suggested for this reason a nonlinear site distribution for vehicle routing problem on the affected points.…”

Intelligent Storage Location Allocation with Multiple Objectives for Flood Control Materials

“…Because emergency supplies tend to be infrequently used, intelligent storage systems are seldom used for emergency supplies, and therefore, there has been little research on storage location allocation in intelligent emergency logistics [32][33][34][35][36]. The emergency supply reserve warehouses of some power agencies have used the Internet of Things to construct intelligent storage systems for their emergency power supplies [37], which has enabled substantial increases in storage automation and storage and retrieval performance, reduced injuries and supply losses, and enhanced the emergency response capabilities.…”