Authors: Hongtao Hu; Xiazhong Chen; Si Zhang
Addresses: Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China ' Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, 201306, China ' School of Management, Shanghai University, Shanghai, 200444, China
Abstract: This paper addresses the quay crane scheduling problem (QCSP) under uncertain conditions at container terminals. Variations in container volume, arrival time, equipment functionality and weather conditions create significant uncertainties when scheduling loading and unloading tasks. In order to maintain the service level of the port under various conditions, port operator urgently need to execute a robust schedule. In this paper, a stochastic programming model is formulated to minimise the makespan of quay crane service, using a particle swarm optimisation (PSO) algorithm integrated with optimal computing budget allocation (OCBA) to improve computational efficiency. Numerical experiments show that the applied algorithm performs well under uncertainty.
Keywords: quay crane scheduling; uncertainty; particle swarm optimisation; PSO; optimal computing budget allocation; OCBA.
International Journal of Shipping and Transport Logistics, 2019 Vol.11 No.2/3, pp.196 - 215
Received: 04 Sep 2017
Accepted: 15 Mar 2018
Published online: 24 Apr 2019 *