The one-dimensional cutting stock problem is a fundamental problem in manufacturing that involves the preparation of raw materials for production. An example of a cutting stock problem in the industry is steel pipe manufacturing, where the raw material preparation operation requires cutting steel sheets from stock rolls based on job specifications. Steel manufacturers usually perform job planning and scheduling on the cutting process to satisfy the production requirement, i.e. job due date, from subsequent operation. The key performance measure is job tardiness. In this paper, we propose a mixed integer linear programming model to solve the one-dimensional cutting stock problem so as to minimize total job tardiness. A numerical example is presented to demonstrate the effectiveness of the model in performing job scheduling to meet the due dates.
Minimizing Job Tardiness in One-Dimensional Cutting Stock Problem Using Mixed Integer Linear Programming (MILP)
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