The simultaneous berth and quay crane allocation problem

Abstract

This paper addresses efficient berth and crane allocation scheduling at a multiuser container terminal. First, we introduce a formulation for the simultaneous berth and crane allocation problem. Next, by employing genetic algorithm we develop a heuristic to find an approximate solution for the problem. The fitness value of a chromosome is obtained by crane transfer scheduling across berths, which is determined by a maximum flow problem-based algorithm based on a berth allocation problem solution defined by the chromosome. The results of numerical experiments show that the proposed heuristic is applicable to solve this difficult but essential terminal operation problem.

A Simulation-Based Optimization Approach for Integrated Port Resource Allocation Problem

“…Recent extensions of the BAP are integrated planning of berth allocation and quay cranes [19][20][21]. For a container terminal, effective berth and quay crane schedules have a great influence on the improvement of both operations.…”

“…In [20] a mix integer programming model has been developed for simultaneous berth and quay crane allocation problem and a genetic algorithm is proposed to find the solution. Heuristic approach for simultaneous optimization of berth and quay crane assignment has been addressed by [22], [23] and [24].…”

An Exact Algorithm for the Integrated Planning of Berth Allocation and Quay Crane Assignment

“…The integrated planning of berth allocation and quay crane assignment, introduced by Park and Kim (2003), has been further investigated by Imai et al (2008) and Meisel and Bierwirth (2009). The resulting models represent a good starting point for tackling such a complex problem; however, they still present some unrealistic assumptions and limits.…”

“…The resulting models represent a good starting point for tackling such a complex problem; however, they still present some unrealistic assumptions and limits. In fact, the relationship between the number of quay cranes and the handling time is ignored (Imai et al, 2008) or the crane productivity is assumed to be proportional to the number of QCs (Park and Kim, 2003), although it is known that quay cranes interference reduces the marginal productivity.…”

A decision support system for managing combinatorial problems in container terminals

“…In [30], Imai et al provide a solution for the integration of BAP with the Quay Crane Assignment Problem (QCAP) based on genetic algorithms. It minimizes the weighted number of vessel rejections.…”