Book — 1 online resource (xiii, 361 pages) : illustrations (some color) Digital: text file.PDF.
Fuzzy Set Theory.- Fuzzy Linear Programming.- Linear Programming with Fuzzy Parameters: Simplex Based Approaches.- Linear Programming with Fuzzy Parameters: Non-Simplex Based Approaches.- Fuzzy Transportation Problem.
(source: Nielsen Book Data)
The book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics. (source: Nielsen Book Data)
Book — 1 online resource (xviii, 232 pages) : illustrations Digital: text file; PDF.
Preliminaries and Backgrounds
Fuzzy Linear Programming
Fuzzy Number Linear Programming
Linear Programming with Fuzzy Variables
Semi-Fully Fuzzy Linear Programming
Application for the Flexible Linear Programming.
This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers. The book essentially generalizes the well-known solution algorithms used in linear programming to the fuzzy environment. Accordingly, it can be used not only as a textbook, teaching material or reference book for undergraduate and graduate students in courses on applied mathematics, computer science, management science, industrial engineering, artificial intelligence, fuzzy information processes, and operations research, but can also serve as a reference book for researchers in these fields, especially those engaged in optimization and soft computing. For textbook purposes, it also includes simple and illustrative examples to help readers who are new to the field.
Book — 1 online resource (XIV, 236 pages 71 illustrations, 1 illustration in color.) : online resource Digital: text file.PDF.
Introduction to Data Envelopment Analysis and Fuzzy Sets
Introductions and Definitions of R
Basic DEA Models with R Codes
Advanced DEA Models with R Codes
Fuzzy Data Envelopment Analysis Models with R Codes.
This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph. D. students in various disciplines, as well as practitioners and researchers.