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Hybrid Heuristics for Marker Planning in the Apparel Industry

  • Research Article-Systems Engineering
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Abstract

Given the diversity of styles and sizes in apparel, marker planning which aims to arrange and move all the pattern parts of garments onto a long thin paper before the cutting process is a very important process for the apparel industry. In order to decrease the wastage of fabric after the cutting process, the marker layout essentially needs to be as compact as possible. In this paper, hybrid heuristics are proposed to conduct and achieve an optimized marker layout and length. First, a moving heuristic is presented as a new packing method to arrange and move the patterns without overlapping; here, an initial marker is presented to calculate the length. This heuristic considers multiple rotated angles and flipping positions of the patterns in order to obtain more diverse arrangements. With different arrangements, there is a higher chance of achieving an optimized marker layout and length. To further improve the solution received from the moving heuristic, soft computing algorithms are taken into account, including the genetic algorithm (GA), simulated annealing (SA), and hybrid genetic algorithm-simulated annealing (HGASA) to achieve a shorter length in the marker layout. The best marker length can be obtained from HGASA, which can save almost 28% of the length. Special cases with specific combinations in rotated angles are considered so that the industry can make informed choices on the algorithms suitable to address the marker planning problem.

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Authors and Affiliations

  1. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei City, Taiwan, Republic of China

    Yu-Chung Tsao, Chia-Hsin Hung & Thuy-Linh Vu

  2. Artificial Intelligence for Operations Management Research Center, National Taiwan University of Science and Technology, Taipei City, Taiwan, Republic of China

    Yu-Chung Tsao

  3. Department of Business Administration, Asia University, Taichung City, Taiwan, Republic of China

    Yu-Chung Tsao

  4. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung City, Taiwan, Republic of China

    Yu-Chung Tsao

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  1. Yu-Chung Tsao
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  2. Chia-Hsin Hung
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  3. Thuy-Linh Vu
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Correspondence to Yu-Chung Tsao.

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Tsao, YC., Hung, CH. & Vu, TL. Hybrid Heuristics for Marker Planning in the Apparel Industry. Arab J Sci Eng 46, 10077–10096 (2021). https://doi.org/10.1007/s13369-020-05210-1

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  • DOI: https://doi.org/10.1007/s13369-020-05210-1

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