This paper takes the vehicles scheduling of hazardous materials as the research object. First, considered the four objectives of risk minimization, cost minimization, risk equilibrium value minimization, and duration minimization, the vehicles robust scheduling of hazardous materials in multiple distribution centers with risk balance is constructed. Then, uncertain models are transformed into peer-to-peer models through the idea of robust discrete optimization. By introducing the crossover and mutation operators of genetic algorithm into particle swarm algorithm, a hybrid particle swarm algorithm is constructed, and three-stage coding rules are adopted. Finally, case study is exemplified to prove the feasibility of the model and algorithm. The results show that the obtained scheduling scheme for the vehicles of hazardous materials minimizes the risk value and makes the risk distribution more balanced for the government regulatory department, and the vehicle can avoid certain road sections with relatively large risk values. For transportation enterprises, the vehicle scheduling scheme for transporting hazardous materials minimizes the cost and shortens the task duration at the same time. In the case of risk uncertainty, different robust control parameters are introduced to make the vehicles robust scheduling of hazardous materials have different degrees of stability.
Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithm
IET Intelligent Transport Systems ; 14 , 14 ; 1955-1966
2021-02-22
12 pages
Article (Journal)
Electronic Resource
English
mutation operators , risk distribution , three-stage coding rules , crossover operators , risk equilibrium value minimisation , peer-to-peer models , scientific scheduling scheme , risk minimisation , road sections , hybrid particle swarm optimisation algorithm , risk balance , minimisation , duration minimisation , hazardous material transportation , government regulatory department , uncertain models , genetic algorithms , flexible road transportation , risk uncertainty , transportation , vehicles robust scheduling , urban roads , scheduling , robust discrete optimisation , genetic algorithm , cost minimisation , adaptable road transportation , transportation enterprises , goods distribution , particle swarm optimisation , robust control parameters , hazardous materials
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