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Hybrid Approach to Optimize Cut Order Plan Solutions in Apparel Manufacturing

ISSN 2223-4985
Journal from gdlhub / 2017-08-14 11:52:32
Oleh : R P Abeysooriya , T G I Fernando, International Journal of Information and Communication Technology Research
Dibuat : 2012-06-23, dengan 1 file

Keyword : Genetic Algorithm, Conventional heuristic algorithms, Cut order Plan
Subjek : Hybrid Approach to Optimize Cut Order Plan Solutions in Apparel Manufacturing
Url : http://esjournals.org/journaloftechnology/archive/vol2no4/vol2no4_3.pdf
Sumber pengambilan dokumen : Internet

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.

Deskripsi Alternatif :

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.

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