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Optimal allocation of material dispatch in emergency events using multi-objective constraint for vehicular networks


In the early stage of large-scale disasters, the first batch of emergency supplies are often in short supply, and decision-makers responsible for material distributions need to send emergency materials to the recipients in the shortest possible time, while also taking into account the minimum transportation costs. In these scenarios, the traditional particle swarm algorithm has been frequently used, however it faces the challenge of “precocious puberty" and is unable to resolve the scheduling problem. To solve this issue, this paper proposes an optimization model for material dispatch in emergency events using a non-dominant sorting algorithm for vehicular communication. The model first satisfies the shortest delivery time and material demand, establishes the shortest route for vehicle travel, and then proposes a multi-objective uncontrolled solving ant colony algorithm to break through the bottleneck of the juvenile algorithm by solving the problems of convergence of NSGA-II algorithm and uneven distribution of Pareto front surface. Moreover, the objective function and constraints for vehicles at each emergency supply point are defined, which must not exceed the total number of available vehicles. The case study shows that the Pareto non-inferior solution searched by NSGA-II is ideal under the premise that multiple goals are optimal, and the Pareto non-inferior solution scheme available for researchers to choose is improved. The model and algorithm objectively optimize the overall layout of emergency material distribution.

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Liu, C., Qian, Y. Optimal allocation of material dispatch in emergency events using multi-objective constraint for vehicular networks. Wireless Netw (2022).

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  • Multi-objective constraints; vehicular networks; emergency events; optimal distribution of materials