Multi-objective hybrid genetic algorithm for quay crane dynamic assignment in berth allocation planning

Authors:
Chengji Liang;Jianquan Guo;Yang Yang
Affiliations:
Logistics Research Center, Shanghai Maritime University, Shanghai, China 200135;Business School, Shanghai University for Science and Technology, Shanghai, China 200093;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan 8080135
Venue:
Journal of Intelligent Manufacturing
Year:
2011

Citing 4
Cited 2

Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Network Models and Optimization: Multiobjective Genetic Algorithm Approach

Network Models and Optimization: Multiobjective Genetic Algorithm Approach
A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning

Computers and Industrial Engineering
The berth planning problem11This research is part of a project the author has with the Port of Singapore Authority. The author was a senior technical consultant in that project. This research was supported in part by the NUS Research Front RP3972679.

Operations Research Letters

Applying modified NSGA-II for bi-objective supply chain problem

Journal of Intelligent Manufacturing
A decision support system for quayside operations in a container terminal

Decision Support Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

The development of containers' transportation has maintained a high momentum since 1961, especially, the containers' traffic growth reached 10---11% in recent years. Container terminals play an important role in the transportation chain, in order to response rapidly for the requirement of modern logistics, better resource allocation, lower cost, and higher operation efficiency are needed. In this paper, we introduce the quay crane dynamic assignment (QCDA) in berth allocation planning problem (BAP) and formulate a multi-objective mathematical model considering each berth for container ship with QCDA and number of Quay Crane's Move. In order to solve this QCDA in BAP problem, we propose a multi-objective hybrid Genetic Algorithm approach with a priority-based encoding method. To demonstrate the effectiveness of proposed mohGA approach, numerical experiment is carried out and the best solution to the problem is obtained.