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Optimal Decisions under Uncertainty

  • Book
  • © 1981

Overview

Authors:
  1. Jati K. Sengupta

    1. Department of Economics, University of California, Santa Barbara, USA

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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 193)

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Table of contents (7 chapters)

  1. Front Matter

    Pages N2-viii
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  2. Optimal Decisions: Theory and Practice

    • Jati K. Sengupta
    Pages 1-3

  3. Linear Programming under Uncertainty

    • Jati K. Sengupta
    Pages 4-37

  4. Risk Aversion in Decision Models

    • Jati K. Sengupta
    Pages 38-77

  5. Linear Allocation Rules under Uncertainty

    • Jati K. Sengupta
    Pages 78-107

  6. Economic Planning under Uncertainty

    • Jati K. Sengupta
    Pages 108-130

  7. Stochastic Programs as Nonzero Sum Games

    • Jati K. Sengupta
    Pages 131-153

  8. Research Trends and Problems

    • Jati K. Sengupta
    Pages 154-156

  9. Back Matter

    Pages 159-161
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Keywords

About this book

The theory of optimal decisions in a stochastic environment has seen many new developments in recent years. The implications of such theory for empirical and policy applications are several. This book attempts to analyze some of the impor­ tant applied aspects of this theory and its recent developments. The stochastic environment is considered here in specific form, e.g., (a) linear programs (LP) with parameters subject to a probabilistic mechanism, (b) decision models with risk aversion, (c) resource allocation in a team, and (d) national economic planning. The book attempts to provide new research insights into several areas, e.g., (a) mixed strategy solutions and econometric tests of hypotheses of LP models, (b) the dual problems of efficient estimation and optimal regulation, (c) input-output planning under imperfect competition, and (d) linear programs viewed as constrained statistical games. Methods of optimal decision rules developed here for quadratic and linear decision problems are applicable in three broad areas: (a) applied economic models in resource allocation, planning and team decision, (b) operations research models in management decisions involving portfolio analysis and stochastic programming, and (c) systems science models in stochastic control and adaptive behavior. Some results reported here have been published in professional journals be-. fore, and I would like to thank the following journals in particular: Inter­ national Journal of Systems Science, Journal of Optimization Theory and Applica­ tions and Journal of Mathematical Analysis and Applications.

Authors and Affiliations

  • Department of Economics, University of California, Santa Barbara, USA

    Jati K. Sengupta

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