An optimization model for aggregate production planning and control: a genetic algorithm approach

Ahmed, S. M.; Biswas, T. K.; Nundy, C. K.

doi:10.22105/riej.2019.192936.1090

Document Type : Research Paper

Authors

Department of Industrial and Production Engineering, Jashore University of Science and Technology, Jahsore, Bangladesh.

https://doi.org/10.22105/riej.2019.192936.1090

Abstract

In this paper, an optimization model for aggregate planning of multi-product and multi-period production system has been formulated. Due to the involvement of too many stakeholders as well as uncertainties, the aggregate production planning sometimes becomes extremely complex in dealing with all relevant cost criteria. Most of the existing approaches have focused on minimizing only production related costs, consequently ignored other cost factors, for instance, supply chain related costs. However, these types of other cost factors are greatly affected by aggregate production planning and its mismanagement often results in increased overall costs of the business enterprises. Therefore, the proposed model has attempted to incorporate all the relevant cost factors into the optimization model which are directly or indirectly affected by the aggregate production planning. In addition, the considered supply chain related costs have been segregated into two major categories. While the raw material purchasing, ordering, and inventory costs have been grouped into an upstream category, finished goods inventory, and delivery costs in the downstream category. The most notable differences with the other existing models of aggregate production planning are in the consideration of the cost factors and formulation process in the mathematical model. A real-life industrial case problem is formulated and solved by using a genetic algorithm to demonstrate the applicability and feasibility of the proposed model. The results indicate that the proposed model is capable of solving any type of aggregate production planning efficiently and effectively.

Keywords

References

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International Journal of Research in Industrial Engineering

An optimization model for aggregate production planning and control: a genetic algorithm approach

References

References

Volume 8, Issue 3
September 2019
Pages 203-224

An optimization model for aggregate production planning and control: a genetic algorithm approach

References

References

Volume 8, Issue 3September 2019Pages 203-224

Volume 8, Issue 3
September 2019
Pages 203-224