In this study, we propose a new algorithm to solve the rectangular strip packing problem (RSPP), a variant of the cutting stock problem in which the mother materials have a common fixed width and infinite length. Based on the column-generation technique with three improvements, the proposed algorithm can solve large-scale problems involving tens of thousands of materials within a reasonable time, considering practical cutting constraints, i.e., the three-stage guillotine cutting constraint and the limitations of slitter blades. The proposed algorithm is evaluated in terms of its packing efficiency and calculation time.
This paper proposes a solution for casting scheduling, an important process in steel manufacturing. A constraint due to secular changes in quality properties, including slab property degradation in casting, and problems with evaluation indices for slab casting width for the improvement of productivity, are taken into account in the study. These factors have not been focused on in previous studies. In this study, the casting scheduling problem is divided into two. One problem involves determining a schedule frame for each slab, and the other is the problem of determining the slab width. To be more specific, after an initial solution for slab order is reached based on heuristics with the quality property constraint taken into account, a hierarchical solving method of determining the slab width is employed in accordance with the shortest path problem-solving method, and obtained solutions are improved using a simulated annealing technique. The simulation is performed with the data created from actual operation data and an initial solution that satisfies the constraint is derived. An improved solution is then obtained using the solution search technique.
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