This study investigated an approach for incorporating statistics with fuzzy sets in the problem. It considers a flow shop problem with imprecise processing times with the objective to minimize the makespan. This work is based on the assumption that the precise value for the processing time of each job is unknown, but that some sample data are available. A combination of statistics and fuzzy sets provides a powerful tool for modeling and solving this problem. The processing times are described by triangular fuzzy numbers. The issue that arises is how to rank the constructed job sequences with respect to their obtained makespans, which are fuzzy numbers. A new distance measure between fuzzy makespans is introduced which includes an optimism/pessimism indicator and a function related to λ-levels of fuzzy sets, enabling the decision maker to express his/her preference. Our work intends to extend the crisp flowshop sequencing problem into a generalized fuzzy model that would be useful in practical situations. In this study, we constructed a fuzzy sequencing model based on statistical data, which uses level (1-α, 1-β) interval-valued fuzzy numbers to represent the unknown job processing time
Flowshop Sequencing Problem Fuzzy Flowshop Model Interval-Valued Fuzzy Number
Diğer ID | JA65ZC22UZ |
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Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 1 Eylül 2011 |
Yayımlandığı Sayı | Yıl 2011 Cilt: 3 Sayı: 3 |