Title :
Particle swarm optimization for Integrated Yard Truck Scheduling and Storage Allocation Problem
Author :
Niu, Ben ; Xie, T. ; Duan, Q.Q. ; Tan, L.J.
Author_Institution :
Coll. of Manage., Shenzhen Univ., Shenzhen, China
Abstract :
The Integrated Yard Truck Scheduling and Storage Allocation Problem (YTS-SAP) is one of the major optimization problems in container port which minimizes the total delay for all containers. To deal with this NP-hard scheduling problem, standard particle swarm optimization (SPSO) and a local version PSO (LPSO) are developed to obtain the optimal solutions. In addition, a simple and effective `problem mapping´ mechanism is used to convert particle position vector into scheduling solution. To evaluate the performance of the proposed approaches, experiments are conducted on different scale instances to compare the results obtained by GA. The experimental studies show that PSOs outperform GA in terms of computation time and solution quality.
Keywords :
genetic algorithms; particle swarm optimisation; scheduling; sea ports; storage; LPSO; NP-hard scheduling problem; SPSO; YTS-SAP; container port; integrated yard truck scheduling and storage allocation problem; local version PSO; particle position vector; problem mapping mechanism; standard particle swarm optimization; total delay minimization; Containers; Delays; Genetic algorithms; Job shop scheduling; Loading; Resource management; Yttrium; Container terminal; Particle Swarm Optimization (PSO); Storage allocation; Yard truck scheduling;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900480