Abstract
In this paper, we studied a stochastic bi-objective mathematical model for effective and reliable rescue operations in multigraph network. The problem is addressed by a two-stage stochastic nonlinear mixed-integer program where the reliability of routes is explicitly traded-off with total weighted completion time. The underlying transportation network is able to keep a group of multiattribute parallel arcs between every pair of nodes. By this, the proposed model should consider the routing decision in logistic planning along with the path selection in an uncertain condition. The first stage of the model concerns with the vehicle routing decisions which is not involved with random parameters; besides, the second stage of the model involves with the departure time at each demand node and path finding decisions after observation of random vectors in the first stage considering a finite number of scenarios. To efficiently solve the presented model, an enhanced nondominated sorting genetic algorithm II (NSGA-II) is proposed. The effectiveness of the introduced method is then evaluated by conducting several numerical examples. The results implied the high performance of our method in comparison to the standard NSGA-II. In further analyses, we investigated the beneficiary of using multigraph setting and showed the applicability of the proposed model using a real transportation case.
Highlights
Natural and human-caused disasters are unforeseen and unexpected events, which would cause catastrophic loss of life, physical destruction, and massive economic disruption
We extend the model of Tikani and Setak [2] from several aspects and study a stochastic reliable time-dependent relief routing problem in multigraphs with semisoft time windows for early post-disaster operations. e main contributions of the current study are as follows: (i) is is the first study that investigates the availability of alternative paths in urban emergency logistics under uncertain conditions
We developed a novel multiobjective stochastic mathematic model for urban distribution of emergency supplies named SR-TDRRPM-SSTW. e first objective strived to minimize the total operational costs and penalties of late arrivals while the second one attempted to maximize the reliability of constructed routes. e arrival times at each demand node of the designated routing scheme were supposed to adhere to semisoft time windows
Summary
Natural and human-caused disasters are unforeseen and unexpected events, which would cause catastrophic loss of life, physical destruction, and massive economic disruption. Emergency Events Database (EM-DAT) was launched by the Center for Research in 1988 on the Epidemiology of Disasters. EM-DAT is a global database on disasters containing essential core data on the occurrence and impacts of mass technological and natural disasters from 1900 to 2015 [1]. In the year 2015, 376 reported natural disasters caused the fatality of 22,765 people, made 110.3 million victims, and caused US $ 70.3 billion damages [1]. According to the statistics, designing an effective logistic network for rescue operations in the early post-disaster situations can significantly reduce the number of victims
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