Using Monarch Butterfly Optimization to Solve the Emergency Vehicle Routing Problem with Relief Materials in Sudden Disasters

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.

Keywords

• emergency vehicle routing problem
• relief materials
• sudden disasters
• intelligent algorithms
• monarch butterfly optimization
• self-adaptive
• crossover operator