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Simulating Theory-of Constraint Problem with Novel Fuzzy Compromise Linear Programming Model

Simulating Theory-of Constraint Problem with Novel Fuzzy Compromise Linear Programming Model

Arijit Bhattacharya, Pandian Vasant, Sani Susanto
Copyright: © 2008 |Pages: 30
ISBN13: 9781599041988|ISBN10: 1599041987|ISBN13 Softcover: 9781616926861|EISBN13: 9781599042008
DOI: 10.4018/978-1-59904-198-8.ch011
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MLA

Bhattacharya, Arijit, et al. "Simulating Theory-of Constraint Problem with Novel Fuzzy Compromise Linear Programming Model." Simulation and Modeling: Current Technologies and Applications, edited by Asim El Sheikh, et al., IGI Global, 2008, pp. 307-336. https://doi.org/10.4018/978-1-59904-198-8.ch011

APA

Bhattacharya, A., Vasant, P., & Susanto, S. (2008). Simulating Theory-of Constraint Problem with Novel Fuzzy Compromise Linear Programming Model. In A. El Sheikh, A. Al Ajeeli, & E. Abu-Taieh (Eds.), Simulation and Modeling: Current Technologies and Applications (pp. 307-336). IGI Global. https://doi.org/10.4018/978-1-59904-198-8.ch011

Chicago

Bhattacharya, Arijit, Pandian Vasant, and Sani Susanto. "Simulating Theory-of Constraint Problem with Novel Fuzzy Compromise Linear Programming Model." In Simulation and Modeling: Current Technologies and Applications, edited by Asim El Sheikh, Abid Thyab Al Ajeeli, and Evon Abu-Taieh, 307-336. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-198-8.ch011

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Abstract

This chapter demonstrates development of a novel compromise linear programming having fuzzy resources (CLPFR) model as well as its simulation for a theory-of-constraints’ (TOC) product mix problem using MATLAB® v. 7.04 R.14 SP.2 software. The product-mix problem considers multiple constraint resources. The developed CLPFR model helps in finding a robust solution with better profit and product mix solution in a non-bottleneck situation. The authors simulate the level of satisfaction of the decision maker (DM) as well as the degree of fuzziness of the solution found using the CLPFR model. Simulations have been carried out with MATLAB® v. 7.04 R.14 SP.2 software. In reality, the capacities available for some resources are not always precise. Some tolerances should be allowed on some constraints. This situation reflects the fuzziness in the availability of resources of the TOC product mix problem.

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