Randomized algorithm with tabu search for multi-objective optimization of large containership stowage plans

  • Authors:

  • Fan Liu;Malcolm Yoke Hean Low;Wen Jing Hsu;Shell Ying Huang;Min Zeng;Cho Aye Win

  • Affiliations:

  • School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore

  • Venue:
  • ICCL'11 Proceedings of the Second international conference on Computational logistics
  • Year:
  • 2011

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Abstract

This paper describes a randomized algorithm with Tabu Search (TS) for multi-objective optimization of large containership stowage plans. The algorithm applies a randomized block-based container allocation approach to obtain a Pareto set of stowage plans from a set of initial solutions in the first stage, and uses TS to carry out multi-objective optimization on the Pareto set of stowage plans in the second stage. Finally, a group of non-dominated solutions is generated based on objectives such as the number of re-handles, the completion time of the longest crane, the number of stacks that exceed the weight limit, the number of idle slots, horizontal moment difference and cross moment difference. Experimental results based on real data show that the proposed algorithm is able to obtain better stowage plans compared with human planners.