Arnat Watanasungsuit
ABSTRACT
In this article, the Gravitational Search Algorithm (GSA) has been applied to find an optimal solution for a one-dimensional cutting-stock problem (1D-CSP). It aims to improve the productivity of the Film Roll cutting design as a 1D-CSP using a mathematical program. The proposed model has been implemented and tested in a case study factory. Four factors, namely, 1) the total number of rolls, 2) the percentage of the total scraps, 3) the percentage of utilization, and 4) the processing time; have been examined. The results show that film roll cutting design using the mathematical programs with GSA takes faster processing time than a traditional staff's ruling cutting design. Also, the initial film roll usage lessens by 9 percent and the number of scraps left from cutting decreases by 1.27 percent when compared with the staff's cutting method. Ultimately, the observed cost-saving during our experiment reduces up to 6,500 USD.
- Esmat Rashedi, Hosseing Nezamabadi-pour, and Saeid Saryazdi. 2009. GSA: a gravitational search algorithm. Information Science, 179, 3 (Jun 2009), 2232-2248. https://doi.org/10.1016/j.ins.2009.03.004.Google Scholar
Digital Library
- Guntram Scheithauer and Johannes Terno. 1991. About the gap between optimal values of the integer and continuous relaxation one-dimensional cutting stock problem. In Proceedings of the Operations Research, Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46773-8_111.Google Scholar
- Harald Dyckhoff. 1990. A typology of cutting and packing problems. European Journal of Operational Research. 44, 2 (Jan 1990), 145-159. https://doi.org/10.1016/0377-2217(90)90350-K.Google ScholarCross Ref
- Teerada Mahayano, Choosak Pornsing, Tongtang Tonglim, and Noppakhun Sanokhiew. 2019. Parameter tuning of gravitational search algorithm for one-dimensional cutting stock problem. In Proceeding of Graduate School Conference. Bangkok, Thailand.Google Scholar
- Teerada Mahayano. 2019. Gravitational Search Algorithm for One-dimensional Cutting Stock Problem. Master Thesis. Graduate School, Silpakorn UniversityGoogle Scholar
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