American Journal of Operations Research

Volume 9, Issue 6 (November 2019)

ISSN Print: 2160-8830   ISSN Online: 2160-8849

Google-based Impact Factor: 0.84  Citations  

A Review of Quantitative Analysis (QA) in Production Planning Decisions Using the Linear Programming Model

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DOI: 10.4236/ajor.2019.96017    1,989 Downloads   7,287 Views  Citations

ABSTRACT

The purpose of this paper was to examine the role of quantitative analysis in production planning decisions. This draws from the observed imperatives of quantitative analysis in business decisions and its capacity for predictability and enhanced decision making given the increasingly complex nature of the business environment. The paper therefore addressed the historical evolution of quantitative technique as an efficient and effective decision-making tool. The content of the paper addressed commonly applied quantitative technique in manufacturing firms today which is, linear programming and its subsequent impact on production planning decisions. The results based on a congruence of views revealed that the “best-fit” application of quantitative analysis models and tools can untangle the complexities of production and planning decision making process in order to achieve the organizational goal. This is, as literature also showed that there is obviously no consensus or integrated model that is capable of solving all managerial problem, different models such as the linear programming model have however been developed to cater for different problems as they arise. The workability or suitability of quantitative analysis is actually premised on its appropriate application. The paper recommends the application of quantitative analysis using linear programming in solving various resource allocation related issues in the primary production planning function of manufacturing firms.

Share and Cite:

Bagshaw, K. (2019) A Review of Quantitative Analysis (QA) in Production Planning Decisions Using the Linear Programming Model. American Journal of Operations Research, 9, 255-269. doi: 10.4236/ajor.2019.96017.

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