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A logic-based Benders decomposition algorithm for anchor position allocation problem
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DOI：10.1016/j.tre.2026.105135.png)
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Abstract
En 中文
An imbalance between the growing demand for vessel access to anchorage areas and the rigid, scarce supply of anchorage capacity has led to persistent anchoring difficulties in port waters. In this paper, we consider the anchor position allocation problem (APAP) that arises from anchorage operations and management. The problem is concerned with serving the demand of a set of calling vessels with the available anchor positions at minimum cost, where some vessels may be denied service if allocation is not cost-effective. The APAP extends traditional variants of the bin packing problem by incorporating practical features: anchor position heterogeneity, vessel navigation directions, and traffic flow control. Despite its theoretical significance and wide-ranging practical relevance, the APAP has received little attention in the literature. We formulate this problem as a mixed-integer linear programming model. General-purpose solvers can handle the model in small-scale scenarios. To address the computational intractability of practical-sized problems, we propose a tailored logic-based Benders decomposition (TLBBD) algorithm with problem-specific optimality cuts, complemented by an exact polynomial-time allocation procedure. Through computational experiments based on the operational data from Zhoushan Port, China, we show that the proposed TLBBD significantly outperforms the Gurobi solver and current industry practices for anchor position allocation. In particular, our algorithm obtains optimal solutions for instances with up to 75 vessels and 30 anchor positions in under ten minutes. Extensive experiments are further conducted to derive managerial insights.
Keywords:
Port operations
Anchorage management
Traffic flow control
Mixed-integer linear programming
Logic-based Benders decomposition
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