Integrating Possibilistic Programming and Throughput Accounting for Return Optimization of Aggregate Production Planning

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Autores principales: Mark Laisin, U. O. Chineh
Formato: Recurso digital
Publicado: Zenodo 2023
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author Mark Laisin
U. O. Chineh
author_facet Mark Laisin
U. O. Chineh
contents This paper presents an integrated approach to aggregate production planning (APP) that combines possibilistic linear programming (PLP) with the throughput accounting system for profit maximization. APP involves making strategic decisions on production levels, inventory management, and resource allocation to meet customer demand while minimizing costs and maximizing profitability. However, the inherent uncertainties and complexities of real-world production environments pose significant challenges to traditional planning models. To address these challenges, this paper proposes the integration of PLP with fuzzy goal programing and the throughput accounting system at the very end, using data received from Rich Pharmaceuticals Ltd, the study's findings were derived using Lingo version 18 software (RPL). The model incorporates possibility distributions of input parameters, allowing decision-makers to consider the uncertainties and imprecisions in demand forecasts, production costs, and capacity constraints. By maximizing profit while considering risk tolerance, it also enables more realistic and reliable production planning decisions
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18327128
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publishDate 2023
publisher Zenodo
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spellingShingle Integrating Possibilistic Programming and Throughput Accounting for Return Optimization of Aggregate Production Planning
Mark Laisin
U. O. Chineh
Aggregate production planning
fuzzy demands
capacity utilization
Decision maker
throughput accounting
This paper presents an integrated approach to aggregate production planning (APP) that combines possibilistic linear programming (PLP) with the throughput accounting system for profit maximization. APP involves making strategic decisions on production levels, inventory management, and resource allocation to meet customer demand while minimizing costs and maximizing profitability. However, the inherent uncertainties and complexities of real-world production environments pose significant challenges to traditional planning models. To address these challenges, this paper proposes the integration of PLP with fuzzy goal programing and the throughput accounting system at the very end, using data received from Rich Pharmaceuticals Ltd, the study's findings were derived using Lingo version 18 software (RPL). The model incorporates possibility distributions of input parameters, allowing decision-makers to consider the uncertainties and imprecisions in demand forecasts, production costs, and capacity constraints. By maximizing profit while considering risk tolerance, it also enables more realistic and reliable production planning decisions
title Integrating Possibilistic Programming and Throughput Accounting for Return Optimization of Aggregate Production Planning
topic Aggregate production planning
fuzzy demands
capacity utilization
Decision maker
throughput accounting
url https://doi.org/10.5281/zenodo.18327128