Vehicle routing multi-objective optimisation for hazardous materials transportation based on adaptive double populations genetic algorithm. (2017)

• Record Type: Journal Article
• Authors: Ma, Changxi; He, Ruichun; Zhu, Chengming; Yang, Xinfeng; Pan, Fuquan
• Is Part Of: International journal of innovative computing and applications. Volume 8:Number 4(2017)
• Page Start: 198
• Page End: 206
• Publication Date: 2017
• Subjects: optimisation -- vehicle routing problem -- VRP -- improved genetic algorithm -- hazardous materials; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Aiming at hazardous materials transportation (HMT), vehicle routing optimisation models for single vehicle and multiple vehicle are proposed respectively, and the adaptive double populations genetic algorithm are constructed. Firstly, the goal functions of models are minimising the total risk, cost and the running time of hazardous materials vehicle. Then, the load constraint, max-risk constraint and time window constraint are considered. Finally, natural number is used for coding, double populations mechanism and adaptive weighted fitness allocation mechanism are adopted to calculate unit fitness, partial matched-crossover method is adopted for crossover operation, and the inversion mutation operator is adopted for mutation operation. Case study shows the model and algorithm are feasible, the vehicle routing strategy can provide direct reference for hazardous materials transportation decision-making departments and it is an effective way for prevention of hazardous materials transportation accidents.