Abstract
Abstract China has one of the highest rates of natural disasters in the world. In recent years, the Chinese government has placed a high value on improving emergency natural disaster relief. The goal of this research was to resolve a key issue for emergency natural disaster relief: the emergency vehicle routing problem (EmVRP) with relief materials in sudden disasters. First, we provided a description of the EmVRP, and defined the boundary conditions. On this basis, we constructed an optimization model of EmVRP with relief materials in sudden disasters. To reach the best solution in the least amount of time, we proposed an enhanced monarch butterfly optimization (EMBO) algorithm, incorporating two modifications to the basic MBO: a self-adaptive strategy and a crossover operator. Finally, the EMBO algorithm was used to solve the EmVRP. Our experiments using two examples EmVRP with relief materials in a sudden-onset disaster proved the suitability of EMBO. In addition, an array of comparative studies showed that the proposed EMBO algorithm can achieve satisfactory solutions in less time than the basic MBO algorithm and seven other intelligent algorithms.
Highlights
China has one of the highest rates of natural disasters in the world
Our experiments using two examples emergency vehicle routing problem (EmVRP) with relief materials in a sudden-onset disaster proved the suitability of enhanced monarch butter y optimization (EMBO)
An array of comparative studies showed that the proposed EMBO algorithm can achieve satisfactory solutions in less time than the basic monarch butter y optimization (MBO) algorithm and seven other intelligent algorithms
Summary
Abstract: China has one of the highest rates of natural disasters in the world. In recent years, the Chinese government has placed a high value on improving emergency natural disaster relief. To reach the best solution in the least amount of time, we proposed an enhanced monarch butter y optimization (EMBO) algorithm, incorporating two modi cations to the basic MBO: a self-adaptive strategy and a crossover operator. We used the proposed EMBO algorithm to solve the EmVRP with relief materials in sudden disasters, and we provided comparative studies between the basic MBO algorithm and seven other intelligent algorithms to demonstrate the superiority of EMBO in terms of accuracy. One of the most representative swarm intelligence algorithms, called monarch buttery optimization (MBO), is introduced to solve emergency vehicle routing problem with relief materials in sudden disasters. The proposed EMBO algorithm is used to tackle EmVRP problem in comparison with the basic MBO algorithm and seven other intelligent algorithms
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