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Multi-Objective Programming in the USSR

  • 1st Edition - January 1, 1991
  • Latest edition
  • Author: Elliot R. Lieberman
  • Editors: Gerald J. Lieberman, Ingram Olkin
  • Language: English

Statistical Modeling and Decision Science: Multi-Objective Programming in the USSR provides information pertinent to multi-objective programming that has emerged as an increasingly… Read more

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Description

Statistical Modeling and Decision Science: Multi-Objective Programming in the USSR provides information pertinent to multi-objective programming that has emerged as an increasingly active area of research in the fields of applied mathematics, operations research, and decision and management science. This book traces and analyzes the development of Soviet multi-objective programming. Organized into 24 chapters, this book begins with an overview of the research institutes most actively involved in multi-objective programming research. This text then presents an analytical framework for grouping and classifying the diverse Soviet methods. Other chapters consider the methods and then evaluated according to the significance and soundness of its basic approach and its kinship to other methods. This book discusses as well some significant Soviet theoretical research and several distinctive approaches proposed by Soviet researchers for comparing the effectiveness of alternative interactive multi-objective programming method. The final chapter deals with distinctive Soviet tendencies in multi-objective research. This book is a valuable resource for economists.

Table of contents

List of TablesList of FiguresPrefaceAcknowledgements 1 Origins of Soviet Multi-Objective Programming 2 A Framework for Approaching Soviet Multi-Objective ProgrammingNo Articulation of Preferences 3 Salukvadze's Ideal Distance Minimization Method 4 Multi-Objective Programming and the Maximal Effectiveness Principle 5 Velichenko's Minimax MethodA Priori Articulation of Preferences 6 Multi-Objective Decomposition for Scalar ProblemsProgressive Articulation of Preferences Using Target Values 7 The Hierarchical Decomposition Approach to High Dimension Multi-Objective Programming Problems 8 The STEM Method 9 Multi-Objective Graph Theory 10 Method of Constraints 11 Parameter Space Investigation Method Ranking of Alternatives or Objectives 12 The Random Search Method 13 The Vector-Relaxation Method 14 The Interactive e-Grid Method Other Forms of Preference Information 15 Adaptive Search Method for Multi-Objective Optimization 16 Pareto Boundary MapsA Posteriori Articulation of Preferences 17 Dynamic Multi-Objective Programming 18 The Reachable Sets Method 19 Piecewise Linear ApproximationOther Noteworthy Research 20 Methodological Research at VNIISI 21 Rastrigin and Eiduk's Methodological Work 22 The Theory of Parametric Scalarization 23 Miscellaneous Other Research 24 Some Concluding ObservationsAppendix A The Method of Constraints A.1 Theoretical Considerations A.2 Illustrative Example: Linear Programming Problem A.3 Method of Sequential Analysis A.4 Illustrative Example: Integer Programming Problem without Side Constraints A.5 Illustrative Example: Integer Programming Problem with Side Constraints A.6 Computational ExperienceB TerminologyC Soviet Books on Multi-Objective SubjectsD Soviet Researchers' Institutional AffiliationsE Cyrillic-Roman Transliteration ConventionsBibliographySoviet SourcesNon-Soviet SourcesIndex

Product details

  • Edition: 1
  • Latest edition
  • Published: May 12, 2014
  • Language: English

About the editor

IO

Ingram Olkin

Affiliations and expertise
Stanford University, California

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