关键词: 集卡预约系统, 拥堵成本, 排放成本, 多约束调度模型, 自适应量子遗传算法

Abstract: Congestion in the morning and evening peak periods increases the uncertainty of the time of truck transportation,and the existing Truck Appointment System (TAS) cannot effectively solve the problem of truck congestion.To reduce container truck congestion,more and more container ports are adopting the use of TAS.A multi-constrained scheduling model based on Mixed Integer Nonlinear Programming (MINLP) was proposed for designing a novel TAS.The appointment change cost,gate queuing cost,congestion cost and idle emission cost in the morning and evening peak periods were considered comprehensively to minimize the overall operating cost for both container truck companies and port companies.The lingo commercial software was used to obtain the exact solutions for small and medium scale problems,and a self-adaptive quantum genetic algorithm was proposed to solve the large-scale problem and obtain the corresponding optimal truck scheduling scheme.Experimental results indicated that the proposed TAS could outperform the conventional TAS by better serving container truck companies and port companies and more effectively reducing their overall operating cost.

Key words: truck appointment system, congestion cost, idle emission cost, multi-constraint scheduling model, self-adaptive quantum genetic algorithm