New Algorithms for the Yard Space Allocation Problem with a Time Dimension
With the acceleration of economic globalization, annual quantum of goods going in and out of a cargo port, i.e., turnover capacity, has been rapidly increasing in areas with highly developed economies, which has resulted in these ports working at full capacity or over capacity. Cargo ports face huge challenges in satisfying the requests from different cargo companies. Therefore, improving the turnover capacity has become the key for cargo ports to maintain competitiveness as well as to meet new business challenges.We study a dynamic space allocation problem at the port yards. During a given period, vessels arrive at a port and unload containers to empty space available in the port yard in stack. The problem has an objective of minimizing total used space. We show this problem is NP-complete and has three dimensions in space and one dimension in time, and propose a new spatial allocation adjustment algorithm. Computational experiments show our algorithm outperforms previous methods by at least 15% and up to 54% in solution quality. The effects of hybridization of several meta-heuristic methods are also discussed.
报告人简介：
王天天是浙江大学管理学院数据科学与管理工程系在读博士研究生，主要研究供应链港口环节的优化问题，擅长建立数学模型并用算法求解。
