An ant colony algorithm for yard truck scheduling and yard location assignment problems with precedence constraints

Zhaojie Xue, Canrong Zhang, Lixin Miao, Wei Hua Lin

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

This paper examines the yard truck scheduling, the yard location assignment for discharging containers, and the quay crane scheduling in container terminals. Taking into account the practical situation, we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations. A Mixed Integer Program (MIP) model is constructed, and a two-stage heuristic algorithm is proposed. In the first stage an Ant Colony Optimization (ACO) algorithm is employed to generate the yard location assignment for discharging containers. In the second stage, the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem, and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms.

Original languageEnglish (US)
Pages (from-to)21-37
Number of pages17
JournalJournal of Systems Science and Systems Engineering
Volume22
Issue number1
DOIs
StatePublished - 2013

Fingerprint

Trucks
Containers
Cranes
Scheduling
Ant colony optimization
Heuristic algorithms
Experiments

Keywords

  • ant colony optimization
  • Container terminal
  • precedence constraints
  • quay crane scheduling
  • yard location assignment
  • yard truck scheduling

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering

Cite this

An ant colony algorithm for yard truck scheduling and yard location assignment problems with precedence constraints. / Xue, Zhaojie; Zhang, Canrong; Miao, Lixin; Lin, Wei Hua.

In: Journal of Systems Science and Systems Engineering, Vol. 22, No. 1, 2013, p. 21-37.

Research output: Contribution to journalArticle

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