A column generation-based heuristic to solve the integrated planning, scheduling, yard allocation and berth allocation problem in bulk ports

João Luiz Marques Andrade () and Gustavo Campos Menezes ()
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João Luiz Marques Andrade: Federal Center for Technological Education of Minas Gerais
Gustavo Campos Menezes: Federal Center for Technological Education of Minas Gerais

Journal of Heuristics, 2023, vol. 29, issue 1, No 2, 39-76

Abstract: Abstract The intelligent management of available resources is one of the greatest challenges of any organization. Find the balance between the size of the stock and the production and transport capacity and ensuring quality service to suppliers and customers. This type of challenge is also very common in port terminals. Ensuring efficient and effective operations is fundamental to reduce fines, avoid accidents, and build customer loyalty. This paper considers integrated planning, scheduling, yard allocation, and berth allocation problem in dry bulk port terminals. The integrated problem consists of planning and scheduling the flow of products between the supply and demand nodes, allocating the products to the storage yards, and determining the loading sequence and berth time and position of each vessel. A mixed-integer linear programming model is proposed, connecting the problems and generating an integrated solution. To solve the integrated problem more efficiently, we developed an algorithm that combines the column generation method with a diving heuristic with limited backtracking, a relax-and-fix heuristic, and an exact algorithm from a commercial solver. The mathematical formulation and the proposed algorithm are tested and validated with large-scale instances. Computational experiments show that the proposed solution approach outperform commercial solver and is very effective in finding strong bounds for large instances.

Keywords: Column generation; Integrated planning; Scheduling; Berth allocation; Stockyard allocation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10732-022-09506-3

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