Particle swarm optimization for the truck scheduling in container terminals

B. Niu, T. Xie, Tung Sun Chan, L. J. Tan, Z. X. Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper we focus on the dispatching problem for trucks at a container terminal, considering a set of transportation requests with different ready times and sequence-dependent processing times. Since the scheduling problem is proved to be NP-hard, exact solution approaches cannot solve it within reasonable time. We proposed a new approach based on particle swarm optimization (PSO) to obtain the optimal solution. Smallest Position Value (SPV) rule is applied as a mapping mechanism to determine the scheduling permutation. Furthermore, a novel algorithm used to convert particle position value into job permutation solution and truck dispatching solution is designed. In the experiment study, two kinds of PSO algorithm are used, i.e. Standard PSO (SPSO) and Local PSO (LPSO). The results obtained by PSOs are also compared with that obtained by genetic algorithm (GA). Experimental results demonstrate that the PSO based approach is efficient to solve the truck scheduling problem than GA in terms of convergence rate, solution quality and CPU time.
Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014
PublisherIEEE
Pages1392-1396
Number of pages5
Volume3
ISBN (Electronic)9781479931965
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014 - Sapporo City, Hokkaido, Japan
Duration: 26 Apr 201428 Apr 2014

Conference

Conference2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014
Country/TerritoryJapan
CitySapporo City, Hokkaido
Period26/04/1428/04/14

Keywords

  • container terminal
  • particle swarm optimization (PSO)
  • truck scheduling

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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