Optimization of Aggregate Production Planning Problems with and without Productivity Loss using Python Pulp Package
Year: 2022
Type: article
Abstract: 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.
Institutions: University of the Punjab, National Textile University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4384934366