Developing a cost-effective and heuristic tool to solve cut order planning problems in the apparel industry

Sandeep Prasad, Monika Panghal and Tesfamichael Molla Ali

International Journal of Mathematics in Operational Research, 2022, vol. 21, issue 1, 26-45

Abstract: Cut order planning (COP) plays a vital role in the proper utilisation of fabric in the garment manufacturing process. It is because its major goal is to develop the most effective cutting plan considering the various decision variables in a purchase order, namely quantity, size and colour. However, the major challenge faced by SMEs is to develop the best mix of cut plans while ensuring the optimum use of the material, machine, and labour in the absence of any sophisticated software. This result in under-utilisation of fabric because of 'intuitive' or 'ballpark figure' approaches adopted to develop a COP, which has negligible scientific validity. The researchers have developed a simple, yet powerful, and cost-effective tool based on a mixed-integer linear programming decision-making model using 'simplex' method with embedded automation powered by macros. The researchers tested the tool and validated the results on two sets of real cutting data.

Keywords: cut order planning; COP; Solver®; macros; Python; area; marker efficiency; garment industry; marker planning; optimisation; Open Computer Vision; OpenCV. (search for similar items in EconPapers)
Date: 2022
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