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INDUSTRIAL ENGINEER – VOLUME: 48 NUMBER: 4
Managers of bulk cargo terminals constantly must make operational decisions. Without an appropriate decision support tool, managers usually resort to simple rules when making these decisions. This can result in a large number of small, scattered storage blocks, high material loss rate and low operational efficiency of the bulk cargo terminal. Optimizing storage space allocation is important, since the decision has a direct impact on the idle and departure time of ships at the terminal. Different materials have different storage space requirements, and space calculations may differ by storage block. The inevitable material mixture at the bottom of piles as space allocation changes causes losses and increases the difficulty of decision-making. Moreover, the availability of storage space in different blocks changes dynamically as time goes by.
This decision problem is investigated in the paper by professor Lixin Tang and other researchers. They incorporated the space allocation structure of container terminals into a unique model formulation and proposed the concept of unit storage space called a slot. They developed an efficient Benders decomposition algorithm for solving the optimization model. The algorithm uses a series of accelerating strategies, including combinatorial Benders cuts, a variable reduction technique and a preprocessing heuristic procedure. By using data from practical terminals, the authors demonstrated the potential benefit of their approach. Compared with the results of current rules, the approach does reduce costs and improve the operational efficiency of bulk cargo terminals.
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