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DOI: 10.14569/IJACSA.2019.0101167
PDF

Optimization of Multi-Product Aggregate Production Planning using Hybrid Simulated Annealing and Adaptive Genetic Algorithm

Author 1: Gusti Eka Yuliastuti
Author 2: Agung Mustika Rizki
Author 3: Wayan Firdaus Mahmudy
Author 4: Ishardita Pambudi Tama

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 11, 2019.

  • Abstract and Keywords
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Abstract: In the planning of aggregate production, company stakeholders need a long time due to the many production variables that must be considered so that the production value can meet consumer demand with minimal production costs. The case study is the company that produces more than a type of product so there are several variables must be considered and computational time is required. Genetic Algorithm is applied as they have the advantage of searching in a solution space but are often trapped in locally optimal solutions. In this study, the authors proposed a new mathematical model in the form of a fitness function aimed at assessing the quality of the solution. To overcome this local optimum problem, the authors refined it by combining the Genetic Algorithm and Simulated Annealing so called hybrid approach. The function of Simulated Annealing is to improve every solution produced by Genetic Algorithm. The proposed hybrid method is proven to produce better solutions.

Keywords: Agreggate; genetic algorithm; hybrid; production planning; simulated annealing

Gusti Eka Yuliastuti, Agung Mustika Rizki, Wayan Firdaus Mahmudy and Ishardita Pambudi Tama, “Optimization of Multi-Product Aggregate Production Planning using Hybrid Simulated Annealing and Adaptive Genetic Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 10(11), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101167

@article{Yuliastuti2019,
title = {Optimization of Multi-Product Aggregate Production Planning using Hybrid Simulated Annealing and Adaptive Genetic Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101167},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101167},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {11},
author = {Gusti Eka Yuliastuti and Agung Mustika Rizki and Wayan Firdaus Mahmudy and Ishardita Pambudi Tama}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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