Hybrid Approach to Optimize Cut Order Plan Solutions in Apparel Manufacturing

The paper examines the combination the conventional heuristic of COP generation and Genetic algorithm (GA) to optimize Cut order plan (COP) solutions in apparel industry. Cut planners in apparel organizations need to decide the cut templates of fabric cutting when the cut order requirement is known. As NP-hard problem with several constrains, COP requires a high speed processing algorithm to find a near optimal solution. This study presents a hybrid type of solution search algorithm to reduce the long execution time of GA based algorithm implemented for COP problem. The suggesting algorithm combined the two search procedures; conventional heuristic and genetic algorithm, to find better solutions for COP. A mask encoding string defined to improve the encoding mechanism of basic GA using conventional heuristic method of COP generation, determined a reduction in population size of the algorithm without changing the convergence power of the algorithm. Experimental results based on several practical cases proved that the proposed hybrid approach lower execution time without changing the searching accuracy given by the GA only method.