Application of simulated annealing to solve multi-objectives for aggregate production planning

Citation

Kalaf, Bayda Atiya and Bakheet, Abdul Jabbar Khudhur and Abbas, Iraq Tereq and Abu Bakar, Mohd Rizam and Lee, Lai Soon and Monsi, Mansor (2016) Application of simulated annealing to solve multi-objectives for aggregate production planning. In: 2nd International Conference on Mathematical Sciences and Statistics (ICMSS2016), 26-28 Jan. 2016, Kuala Lumpur, Malaysia. (pp. 1-6).

Abstract

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and requires minimal time.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science
DOI Number:	https://doi.org/10.1063/1.4952566
Publisher:	AIP Publishing
Keywords:	Aggregate production planning; Simulated annealing; Production planning; Multi-objective linear programming
Depositing User:	Nabilah Mustapa
Date Deposited:	26 Sep 2017 04:02
Last Modified:	26 Sep 2017 04:02
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4952566
URI:	http://psasir.upm.edu.my/id/eprint/57308
Statistic Details:	View Download Statistic

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