When less is better: Insights from the product mix dilemma from the Theory of Constraints perspective


Autoria(s): de Souza, Fernando Bernardi; Sobreiro, Vinicius Amorim; Nagano, Marcelo Seido; de Souza Manfrinato, Jair Wagner
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

03/07/2013

Resumo

Perhaps due to its origins in a production scheduling software called Optimised Production Technology (OPT), plus the idea of focusing on system constraints, many believe that the Theory of Constraints (TOC) has a vocation for optimal solutions. Those who assess TOC according to this perspective indicate that it guarantees an optimal solution only in certain circumstances. In opposition to this view and founded on a numeric example of a production mix problem, this paper shows, by means of TOC assumptions, why the TOC should not be compared to methods intended to seek optimal or the best solutions, but rather sufficiently good solutions, possible in non-deterministic environments. Moreover, we extend the range of relevant literature on product mix decision by introducing a heuristic based on the uniquely identified work that aims at achieving feasible solutions according to the TOC point of view. The heuristic proposed is tested on 100 production mix problems and the results are compared with the responses obtained with the use of Integer Linear Programming. The results show that the heuristic gives good results on average, but performance falls sharply in some situations. © 2013 Copyright Taylor and Francis Group, LLC.

Identificador

http://dx.doi.org/10.1080/00207543.2013.802052

International Journal of Production Research.

0020-7543

1366-588X

http://hdl.handle.net/11449/75909

10.1080/00207543.2013.802052

WOS:000325069700012

2-s2.0-84879469066

Idioma(s)

eng

Relação

International Journal of Production Research

Direitos

closedAccess

Palavras-Chave #excess capacity #Integer Linear Programming #optimization #production mix #Theory of Constraints
Tipo

info:eu-repo/semantics/article