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Theory and practice of uncertain programming
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TLDR
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
Citations
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Proceedings ArticleDOI
Convergence of Optimal Solutions about Approximation Scheme for Fuzzy Programming with Minimum-Risk Criteria
Yan-Kui Liu,Miao Tian +1 more
TL;DR: The purpose of this paper is to establish conditions under which the optimal objective value and optimal solution of such approximating two-stage FMRP converges to the optimal Objective Value and optimal Solution of the original two- stage FMRPs, respectively.
Journal ArticleDOI
An Uncertain Programming Model for Competitive Logistics Distribution Center Location Problem
Bingyu Lan,Jin Peng,Lin Chen +2 more
TL;DR: The expected value model is constructed to maximize the expected profit of the new distribution center and can be transformed into its deterministic form by taking advantage of the operational law of uncertain variables.
Dissertation
Gestion des risques dans les chaînes logistiques : planification sous incertitude par la théorie des possibilités
TL;DR: In this article, the authors propose a method to integrate connaissances imparfaite sur les donnees (date du besoin en composants, quantite necessaire, etc.) in order to calculate le plan d'approvisionnement plus robuste (plan minimisant l'impact de lincertitude).
Journal ArticleDOI
Trade credit policy of an inventory model with imprecise variable demand: an ABC-GA approach
TL;DR: The inventory model with fuzzy promotional effort induced dynamic demand under two level partial trade credit policy has been developed in an imprecise planning horizon and a heuristic, multichoice artificial bee genetic algorithm (MCABGA) has been proposed for it.
Proceedings ArticleDOI
Consistent Inverse Probability and Possibility Propagation
Dominik Hose,Michael Hanss +1 more
TL;DR: It is shown that by reverting back to the coarser framework of possibility theory this problem possesses a conceptually straightforward solution with some powerful properties in the view of imprecise probability descriptions.
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.
Journal ArticleDOI
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.