Multi-objective Aggregate Production Planning Model Considering Overtime and Outsourcing Options Under Fuzzy Seasonal Demand

Date

2019-01-01

Author

Tirkolaee, Erfan Babaee
Goli, Alireza
Weber, Gerhard Wilhelm

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper investigates a novel fuzzy multi-objective multi-period Aggregate Production Planning (APP) problem under seasonal demand. As two of the main real-world assumptions, the options of workforce overtime and outsourcing are studied in the proposed Mixed-Integer Linear Programming (MILP) model. The main goals are to minimize the total cost including in-house production, outsourcing, workforce, holding, shortage and employment/ unemployment costs, and maximize the customers' satisfaction level. To deal with demand uncertainty, triangular fuzzy numbers are considered for demand parameters. Then the proposed model is validated by solving an illustrative example using a Weighted Goal Programming (WGP) method and CPLEX solver. Finally, it is demonstrated that uncertain conditions and considering real-world assumptions can yield different results in developing a practical aggregate production plan. Moreover, a sensitivity analysis is then performed to provide qualitative managerial insights and decision aids.

Subject Keywords

Aggregate production planning, Fuzzy seasonal demand, Outsourcing, Weighted Goal Programming, Sensitivity analysis

URI

https://hdl.handle.net/11511/57396

DOI

https://doi.org/10.1007/978-3-030-18789-7_8

Conference Name

6th International Scientific-Technical Conference on Advances in Manufacturing II

Collections

Graduate School of Applied Mathematics, Conference / Seminar

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Citation Formats

E. B. Tirkolaee, A. Goli, and G. W. Weber, “Multi-objective Aggregate Production Planning Model Considering Overtime and Outsourcing Options Under Fuzzy Seasonal Demand,” presented at the 6th International Scientific-Technical Conference on Advances in Manufacturing II, Poznan, POLAND, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57396.