A hybrid genetic algorithm for the cut order planning problem

Authors:
Ahlem Bouziri;Rym M'hallah
Affiliations:
Institut Supérieur des Arts Multimédia, Manouba University, Charguia II, Tunisia;Department of Statistics and Operations Research, Kuwait University, Safat, Kuwait
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

This paper proposes a new hybrid heuristic to a difficult but frequently occurring problem in the apparel industry: the cut order planning (COP). This problem consists of finding the combination of ordered sizes on the material layers that minimizes total material utilization. The current practice in industry solves COP independently from the two-dimensional layout (TDL) problem; i.e., COP estimates the length of the layout required to cut a particular combination of sizes instead of packing the pieces on the fabric and determining the actual length used. Evidently, this results in a build up of estimation errors; thus increased waste. Herein, COP and TDL are combined into a single problem CT. The resulting problem is modeled and solved using a hybrid heuristic which combines the advantages of population based approaches (genetic algorithms) with those of local search (simulated annealing). The experimental results show the validity of the proposed model, and the sizeable savings it induces when solved using the proposed hybrid heuristic.