Bavandi, S., Nasseri, S.H., Triki, C. (2020) Optimal decision making in fuzzy stochastic hybrid uncertainty environments and their application in transportation problems. Advances in Intelligent Systems and Computing, 1094 . pp. 65-72. ISSN 2194-5357. (doi:10.1007/978-981-15-2459-2_5) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:91499)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: http://dx.doi.org/10.1007/978-981-15-2459-2_5 |
Abstract
Decision making plays an important role in economic, management, business, marketing, psychology, philosophy, mathematics, statistics, and many other fields. In each field, decision making consists of identifying the values, uncertainties, and other issues that define the decision. Randomness and fuzziness or vagueness are two major sources of uncertainty in the real world. Practical applications in areas of industrial engineering, management, and economics, are such that decision-makers are being confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and a decision making has to be performed under such a twofold uncertain environment of co-occurrence of randomness and fuzziness. This paper presents an application to the transportation problems in fuzzy stochastic hybrid uncertainty environments. In this paper, we focus on our attention on unbalanced transportation problems in the fuzzy stochastic environment. © Springer Nature Singapore Pte Ltd. 2020.
Item Type: | Article |
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DOI/Identification number: | 10.1007/978-981-15-2459-2_5 |
Uncontrolled keywords: | Fuzzy set theory; Fuzzy systems; Random processes; Stochastic systems, Co-occurrence; Decision makers; Optimal decision making; Sources of uncertainty; Stochastic environment; Transportation problem; Uncertain environments; Uncertainty environment, Decision making |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Chefi Triki |
Date Deposited: | 18 Nov 2021 09:41 UTC |
Last Modified: | 05 Nov 2024 12:57 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/91499 (The current URI for this page, for reference purposes) |
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