Optimization of Aggregate Production Planning Problems with and without Productivity Loss using Python Pulp Package

• Autorzy: Rehman Hakeem Ur , Ahmad Ayyaz , Ali Zarak , Baig Sajjad Ahmad , Manzoor Umair

Identyfikatory

DOI

10.24425/mper.2021.139993

• Języki publikacji: EN

Abstrakty

EN

Traditionally the aggregate production plan helps in determining the inventory, production, and work-force, based on the demand forecasts without considering the productivity loss at a tactical level in supply chain planning. In this paper, we include the productivity loss into traditional aggregate production plan and the prescriptive analytics technique, linear programming, is used to solve this problem of practical interest in the domain of multifarious businesses and industries. In this study, we discussed two model variations of the aggregate production planning problem with and without productivity loss, i) fixed work-force, and ii) variable Work Force. The mathematical models were designated to be solved by using an open-source python pulp package in order to evaluate the impacts of the productivity loss on both the models. PuLP is an open-source modeling framework provided by the COIN-OR Foundation (Computational Infrastructure for Operations Research) for linear and integer Programing problems written in Python. The computational results indicate that the productivity loss has direct impact on the workforce hiring and firing.

Słowa kluczowe

EN

aggregate production planning; productivity; Python PuLP; optimization

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2021
• Tom: Vol. 14, No. 4
• Strony: 38--44
• Opis fizyczny: Bibliogr. 16 poz., tab., wykr.

Twórcy

autor

Rehman Hakeem Ur

• Institute of Quality & Technology Management, University of the Punjab, Lahore, Pakistan

autor

Ahmad Ayyaz

• Institute of Quality & Technology Management, University of the Punjab, Lahore, Pakistan

autor

Ali Zarak

• Institute of Quality & Technology Management, University of the Punjab, Lahore, Pakistan

autor

Baig Sajjad Ahmad

• National Tex tile University, Faisalabad, Pakistan

autor

Manzoor Umair

• Faisalabad Business School, National Textile University, Faisalabad, Pakistan

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)