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Chinese Journal of Management Science ›› 2015, Vol. 23 ›› Issue (10): 125-130.doi: 10.16381/j.cnki.issn1003-207x.2015.10.014

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Optimization Model and Algorithms of Truck Appointment in Container Terminals

ZENG Qing-cheng1,2, CHEN Wen-hao1, HU Xiang-pei2   

  1. 1. School of Transport Management, Dalian Maritime University, Dalian 116026, China;
    2. Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, China
  • Received:2013-03-12 Revised:2014-07-13 Online:2015-10-20 Published:2015-10-24

Abstract: Truck congestion of container terminals is an important issue which increases truck waiting time, decreases the operation efficiency of container terminal and increases the carbon emissions. Truck appointment is one of the effective methods to alleviate the gate congestion. In this paper, issues of truck appointment optimization are addressed. An optimization model for truck appointment quota is developed. In this model, the appointment quota for each time period is optimized, considering the constraints of adjustment quota. The non-stationary queuing model is used to describe the time-dependent characteristics of truck arrival. To solve the model, a method based genetic algorithm and Point wise Stationary Fluid Flow Approximation (PSFFA) is designed. Genetic algorithm is used to search the optimal solution and PSFFA is used to calculate the truck queuing time. In order to illustrate the validity of the proposed model and algorithms, numerical experiments with the data of one container terminal in Shenzhen from July 28 to August 2 in 2007. Results indicate that the proposed model can decrease the truck queuing time and PSFFA can solve the no-stationary queue problem efficiently. The optimization model developed in the paper can provide basis for decision-making of truck appointment, make a contribution to deepening the research on theory of truck appointment, and have a guiding significance in the practice of truck appointment.

Key words: container terminals, truck appointment, queuing model, point wise stationary fluid flow approximation

CLC Number: