TY  - JOUR
N2  - The present research work outlines a fuzzified approach using fuzzy linear programming (FLP) using a suitably designed smooth logistic membership function (MF) for finding fuzziness patterns at disparate levels of satisfaction for theory of constraints-based (TOC) product-mix decision problems. The objective of the present work is to find fuzziness patterns of product-mix decisions with disparate levels of satisfaction of the decision-maker (DM). Another objective is to provide a robust, quantified monitor of the level of satisfaction among DMs and to calibrate these levels of satisfaction against DM expectations. Product-mix decision should take into account considerations such as the DM's level of satisfaction (sometimes called 'emotions') in order to make the decision a robust one. Sensitivity of the decision has been focused on a bottleneck-free, optimal product-mix solution of a TOC problem. The inefficiency of traditional linear programming (LP) in handling multiple-bottleneck problems using TOC is discussed using an illustrative example. Relationships among the degree of fuzziness, level of satisfaction and the throughput of modified TOC guide decision-makers (DM) under tripartite fuzzy environment in obtaining their product-mix choice trading-off with a pre-determined allowable fuzziness.
ID  - scholars482
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-36248943998&doi=10.1080%2f00207540600823187&partnerID=40&md5=be4b1782d52415c461a2178a1ce57c57
EP  - 815
JF  - International Journal of Production Research
IS  - 3
SN  - 00207543
N1  - cited By 35
TI  - A fully fuzzified, intelligent theory-of-constraints product-mix decision
VL  - 46
KW  - Decision theory; Intelligent systems; Problem solving; Robustness (control systems)
KW  -  Fuzzified linear programming; Intelligent decision
KW  -  Constraint theory
A1  - Bhattacharya, A.
A1  - Vasant, P.
A1  - Sarkar, B.
A1  - Mukherjee, S.K.
SP  - 789
AV  - none
Y1  - 2008///
ER  -