A simulation-based Genetic Algorithm approach for the quay crane scheduling under uncertainty

Noura Al-Dhaheri, Aida Jebali, Ali Diabat

Research output: Contribution to journalArticlepeer-review


The fast-paced growth in containerized trade market sparks the need for efficient operations at seaport container terminals. One major determinant of terminal efficiency is the productivity of Quay Cranes (QC) resulting from QC scheduling. This paper focuses on the QC Scheduling Problem (QCSP). The objective is to minimize vessel handling time while considering the entire container handling process involving both seaside operations and container transfer operations, taking place between the quay and the stacking yard. A stochastic mixed integer programming model is proposed, and a simulation-based Genetic Algorithm (GA) is applied to construct QC schedules that account for the dynamics and the uncertainty inherent to container handling process. Computational experiment shows satisfactory results of the proposed algorithm and stresses the importance of simulation to obtain more reliable estimates of QC schedule performance.

Original languageEnglish (US)
Pages (from-to)122-138
Number of pages17
JournalSimulation Modelling Practice and Theory
StatePublished - Aug 1 2016


  • Quay Crane scheduling
  • Simulation-based Genetic Algorithm
  • Stochastic programming
  • Straddle carriers

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Hardware and Architecture


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