Optimisation for quay crane scheduling problem under uncertainty using PSO and OCBA. (17th April 2019)

• Record Type: Journal Article
• Authors: Hu, Hongtao; Chen, Xiazhong; Zhang, Si
• Is Part Of: International journal of shipping and transport logistics. Volume 11:Number 2/3(2019)
• Page Start: 196
• Page End: 215
• Publication Date: 2019-04-17
• Subjects: quay crane scheduling -- uncertainty -- particle swarm optimisation -- PSO -- optimal computing budget allocation -- OCBA; Shipping -- Periodicals; Shipping -- Statistics; Logistics -- Periodicals; 387.5
• Languages: English
• ISSNs: 1756-6517

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.