Affiliation:
1. Department of Mathematical Sciences, University of Essex, Essex, UK
Abstract
There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Regulating the imbalance for the container relocation problem: A deep reinforcement learning approach;Computers & Industrial Engineering;2024-05
2. Container transaction type prediction: a seaport case in Turkey;International Journal of Shipping and Transport Logistics;2023
3. Quantum Computing and Machine Learning for Efficiency of Maritime Container Port Operations;2022 Systems and Information Engineering Design Symposium (SIEDS);2022-04-28
4. Optimization of cabinet reshuffle assignment problem;INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE “TECHNOLOGY IN AGRICULTURE, ENERGY AND ECOLOGY” (TAEE2022);2022