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Theory and practice of uncertain programming
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This book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem.Abstract:
Real-life decisions are usually made in the state of uncertainty such as randomness and fuzziness. How do we model optimization problems in uncertain environments? How do we solve these models? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem. Researchers, practitioners and students in operations research, management science, information science, system science, and engineering will find this work a stimulating and useful reference.read more
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Journal ArticleDOI
Uncertain goal programming models for bicriteria solid transportation problem
TL;DR: It is proved that the expected value goal Programming model and chance-constrained goal programming model can be respectively transformed into the corresponding deterministic equivalents by taking advantage of some properties of uncertainty theory.
Journal ArticleDOI
Uncertain random multilevel programming with application to production control problem
Hua Ke,Taoyong Su,Yaodong Ni +2 more
TL;DR: For modeling decentralized decision-making problems with uncertain random parameters, an uncertain random multilevel programming is proposed and an equivalent crisp mathematical programming to the established uncertain random programming is presented.
Journal ArticleDOI
Covering location problem of emergency service facilities in an uncertain environment
Bo Zhang,Jin Peng,Shengguo Li +2 more
TL;DR: In this paper, the location set covering problem in an uncertain environment is modeled as an uncertain location set cover problem, which is then solved by using the inverse uncertainty distribution of the covered demand.
Journal ArticleDOI
Uncertain multilevel programming
Baoding Liu,Kai Yao +1 more
TL;DR: This paper aims at providing an uncertain multileVEL programming model that is a type of multilevel programming involving uncertain variables and a genetic algorithm is employed to solve the model.
Journal ArticleDOI
Dual-channel structure choice of an environmental responsibility supply chain with green investment
TL;DR: Zhang et al. as discussed by the authors modeled the environmental responsibility behaviors of both manufacturer and consumers to study the dual-channel structure strategy of a green manufacturer and further examined its environmental performance under fuzzy uncertainties.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
Multilayer feedforward networks are universal approximators
TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Book
Dynamic Programming
TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
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The concept of a linguistic variable and its application to approximate reasoning—II☆
TL;DR: Much of what constitutes the core of scientific knowledge may be regarded as a reservoir of concepts and techniques which can be drawn upon to construct mathematical models of various types of systems and thereby yield quantitative information concerning their behavior.