An integer multi-objective optimization model and an enhanced non-dominated sorting genetic algorithm for contraflow scheduling problem
来源期刊：中南大学学报(英文版)2015年第6期
论文作者：Li Pei-heng Lou Ying-yan
文章页码：2399 - 2405
Key words：hurricane evacuation; contraflow scheduling; multi-objective optimization; NSGA-II
Abstract: To determine the onset and duration of contraflow evacuation, a multi-objective optimization (MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.
Li Pei-heng(李沛恒), Lou Ying-yan(楼颖燕)
(School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe AZ 85287-3005, USA)
Abstract:To determine the onset and duration of contraflow evacuation, a multi-objective optimization (MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.
Key words:hurricane evacuation; contraflow scheduling; multi-objective optimization; NSGA-II
