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In classical bi-level programming problems, coefficients of objective functions of the leader and the follower are crisp. But in real-life situations, uncertainties arise in almost every aspect. Thus, to include more realistic cases in classical bi-level programming problems, a fuzzy stochastic bi-level programming model has been developed using fuzzy random variable coefficients. A fuzzy random variable is a mathematical tool to deal with a sort of hybrid uncertainty. The novelty of the fuzzy random variable is that it contains the structure of twofold distribution which can carry a joint oneness of the simultaneous random and imprecise information which goes beyond the contrast of information contained in a random variable in probability theory and fuzzy variable in fuzzy set theory. Though the book deals to solve bi-level optimization models in the fuzzy or fuzzy random environment through a multi-stage decision-making approach. The main contribution of this book is twofold. It introduced the fuzzy stochastic and fuzzy rule-base bi-level optimization model to overcome the uncertainties present due to impreciseness and randomness.
| Autorius: | Vishnu Pratap Singh, Debjani Chakraborty, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2021 |
| Knygos puslapių skaičius: | 84 |
| ISBN-10: | 6203307483 |
| ISBN-13: | 9786203307481 |
| Formatas: | 220 x 150 x 6 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Bi-level Optimization in an Imprecise and Random Environment“
