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Modeling and Optimization of the Lifetime of Technologies

  • Natali Hritonenko
  • Yuri Yatsenko

Part of the Applied Optimization book series (APOP, volume 4)

Table of contents

  1. Front Matter
    Pages i-xxxvi
  2. Integral Dynamical Models of Evolving Systems

    1. Front Matter
      Pages 1-1
    2. Natali Hritonenko, Yuri Yatsenko
      Pages 3-12
    3. Natali Hritonenko, Yuri Yatsenko
      Pages 13-26
    4. Natali Hritonenko, Yuri Yatsenko
      Pages 27-34
  3. Analysis of One-Sector Integral Dynamical Models

    1. Front Matter
      Pages 35-35
    2. Natali Hritonenko, Yuri Yatsenko
      Pages 37-52
    3. Natali Hritonenko, Yuri Yatsenko
      Pages 53-74
    4. Natali Hritonenko, Yuri Yatsenko
      Pages 75-100
  4. Analysis of Multi-Sector Integral Dynamical Models

    1. Front Matter
      Pages 101-101
    2. Natali Hritonenko, Yuri Yatsenko
      Pages 115-134
    3. Natali Hritonenko, Yuri Yatsenko
      Pages 135-148
    4. Natali Hritonenko, Yuri Yatsenko
      Pages 149-162
    5. Natali Hritonenko, Yuri Yatsenko
      Pages 163-180
  5. Applied Problems of Integral Dynamic Models

    1. Front Matter
      Pages 193-193
    2. Natali Hritonenko, Yuri Yatsenko
      Pages 195-214
    3. Natali Hritonenko, Yuri Yatsenko
      Pages 227-232
  6. Back Matter
    Pages 233-249

About this book

Introduction

Modern economic growth is characterized by structural changes based on the introduction of new technologies into economics. The replacement and renova­ tion of technologies in industrial environments undergoing technical change is clearly one of the key aspects of economic development. The mathematical modeling of evolutionary economics under technical change (TC) has been rigorously considered by many authors during last decades. There is a wide variety of economic approaches and models describing different aspects of technical change. Among these are the models of embodied technical progress [19], [35], [70], [129], endogenous growth models [94], [102], the models of technological innovations [31], [32], [41], and others. The perspective self­ organization evolutionary approach is developed in [20], [38], [122], [123], [124], [126], which unites the aspects of diffusion of new technologies, technological and behavioral diversity of firms, learning mechanisms, age-dependent effects, and other important features of real-life economics. On the whole, an interest in evolutionary economics has brought considerable progress in the description and conceptualization of the sources, characteristics, direction and effects of technical change [125]. However, the modeling and control of technology lifetime under technical change has received rather little attention in mathematical economics in con­ trary to other aspects of technical progress. The lifetime of technologies has rarely been formally treated as a part of more general mathematical theory of economic dynamics. A problem which is still to be resolved consists in establishing the rational strategies of technologies' replacement under various assumptions on the behavior of technical change.

Keywords

algorithms calculus economic dynamics economic system economics evolutionary economics integral equation integration Mathematica mathematical economics mathematical modeling model modeling optimization strategy

Authors and affiliations

  • Natali Hritonenko
    • 1
  • Yuri Yatsenko
    • 2
  1. 1.Department of CyberneticsKiev UniversityKievUkraine
  2. 2.Glushkov Institute of CyberneticsUkrainian Academy of SciencesKievUkraine

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4613-3446-0
  • Copyright Information Springer-Verlag US 1996
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-3448-4
  • Online ISBN 978-1-4613-3446-0
  • Series Print ISSN 1384-6485
  • Buy this book on publisher's site
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