Abstract
Increased frequency of disasters keeps reminding us of the importance of effective resource distribution in postdisaster. To reduce the suffering of victims, this paper focuses on how to establish an effective emergency logistics system. We first propose a multiobjective optimization model in which the location and allocation decisions are made for a three-level logistics network. Three objectives, deprivation costs, unsatisfied demand costs, and logistics cost, are adopted in the proposed optimization model. Several cardinality and flow balance constraints are considered simultaneously. Then, we design a novel effective IFA-GA algorithm by combining the firefly algorithm and genetic algorithm to solve this complex model effectively. Furthermore, three schemes are proposed to improve the effectiveness of the IFA-GA algorithm. Finally, the numerical results provide several insights on the theory and practice of relief distribution, which also illustrate the validity of the proposed solution algorithm.
Highlights
Large-scale natural or man-made disasters, such as the 2010 Haitian Earthquake, the 2011 tsunami in Japan, the civil war in Syria, and the 2019 coronavirus disease, have occurred frequently throughout the world, resulting in tremendous consequences of enormous casualties and property losses.e world has witnessed a steadily increased number in both disasters and affected people since the 1900s
Because each regional transfer center (RTC) is linked to Strategic National Stockpile (SNS), which is located at point (0, 0) in our setting, we ignore the paths between SNS and RTCs for simplification
For the small-scale case, the iteration results of IFA-Genetic Algorithm (GA), Firefly Algorithm (FA), GA, and PSD are shown in Algorithm IFA-GA FA GA particle swarm optimization (PSO)
Summary
Large-scale natural or man-made disasters, such as the 2010 Haitian Earthquake, the 2011 tsunami in Japan, the civil war in Syria, and the 2019 coronavirus disease, have occurred frequently throughout the world, resulting in tremendous consequences of enormous casualties and property losses. Ismail [3] studied a relief distribution problem by considering the logistics and deprivation costs. Moreno et al [11] presented a novel model to optimize location, transportation, and fleet sizing for emergency logistics with considering deprivation costs. Zhu et al [13] studied the emergency relief routing optimization problem considering injured degree and deprivation cost. Ree objectives, deprivation costs, unsatisfied demand losses, and logistics costs, are adopted in the proposed optimization model. Zhou et al [2] studied the multiperiod dynamic emergency resource scheduling problem by a proposed multiobjective optimization model. E contributions of this paper can be summarized as follows: first, we propose a new multiobjective location-allocation optimization model for emergency logistics, in which deprivation costs, fairness, and operation costs are considered.
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