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Applications of Decision Making with Uncertain Information
Author(s) -
Yang Lixing,
Li Xiang,
A. Ralescu Dan
Publication year - 2015
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21677
Subject(s) - beijing , library science , citation , chinese academy of sciences , state (computer science) , operations research , china , key (lock) , control (management) , computer science , mathematics , political science , artificial intelligence , law , algorithm , computer security
In the process of decision making, a variety of unpredictable factors can result in imprecise information, which can be classified into randomness, fuzziness and uncertainty within mathematical frameworks. Accordingly, probability theory, fuzzy set theory and uncertainty theory, respectively, have been used to describe and handle these types of uncertainties. Moreover, as multi-fold uncertainties can often occur simultaneously in a complicated system, fuzzy random theory and uncertain random theory have been also developed to handle mixed models of uncertainty. Typically, all these approaches can provide efficient methodologies to handle real-world uncertain information. This special issue aims to cover all aspects of employing uncertain technologies to find optimal solutions and assist in making the best possible decisions. It also intends to provide the readership with the recent and significant research on the theoretical results in the framework of uncertain technologies and their applications to a variety of real-world problems, including transportation, management, information systems, economics, supply chain, finance, among others. After the call for papers was announced in late January, 2013, this special issue has been attracted tremendous attentions from a lot of researchers. Totally, we had received 15 manuscripts before the submission deadline. After a rigorous review process, only five papers are finally accepted for publication in this special issue. The first paper by Lixing Yang et al. proposed an integer programming model for train scheduling on a single-track railway line by using space-time network representation. In their research, the velocity choice is considered to decrease the expected energy consumption and interactions between different trains, where link energy consumption is deduced by Davis formula. The second paper by Meiyi Wei et al. proposed a chance-constrained programming model for the hazardous materials transportation within the framework of credibility theory, which aims to obtain the tradeoff between the transportation risk and cost. The third paper by Yuhan Liu et al. formulated an uncertain currency model by considering the foreign exchange rate as an uncertain processes described by uncertain differential equations driven by Liu process. Furthermore, European and American currency option pricing formulas were derived for the proposed uncertain currency model. The fourth paper by Jinwu Gao and Kai Yao proposed an uncertain random process as a generalization of both stochastic process and uncertain process, and some special types of uncertain random processes such as stationary increment process and renewal process were also discussed. The fifth paper by Hua Ke et al. considered a project scheduling problem in the environment with uncertainty and randomness, and a hybrid intelligent algorithm was proposed to search the quasi-optimal schedules. Finally, we in particular thank Editor-in-Chief and all the reviewers for their kind supports in the process of organization and review for this special issue.

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