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Capacitated Planned Maintenance

Models, Optimization Algorithms, Combinatorial and Polyhedral Properties

  • Torben Kuschel

Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 686)

Table of contents

  1. Front Matter
    Pages i-xxix
  2. Torben Kuschel
    Pages 1-6
  3. Torben Kuschel
    Pages 25-70
  4. Torben Kuschel
    Pages 267-271
  5. Back Matter
    Pages 273-286

About this book

Introduction

This book examines the problem of maintenance planning and scheduling in industrial production systems. It presents two practically relevant, deterministic mathematical models: the capacitated planned maintenance problem (CPMP) and the weighted uncapacitated planned maintenance problem (WUPMP). It introduces specific optimization algorithms such as construction heuristics, Lagrangean and tabu search metaheuristics. A problem independent hybrid approach links and alternates between two Lagrangean relaxations. It also analyzes the solvability with respect to the computational complexity of several problem classes, polyhedral properties and lower bounds. Computational studies demonstrate the performance of the heuristics, lower bounds, subgradients obtained from heuristics and the quality of dual information. This unique book includes implementation details and an introduction to the necessary theory making it suitable for upper undergraduate students.

Keywords

planned maintenance optimization algorithms polytopes combinatorics maintenance planning polyhedral properties CPMP WUPMP

Authors and affiliations

  • Torben Kuschel
    • 1
  1. 1.WINFOR–Business Computing and Operations ResearchUniversity of WuppertalWuppertalGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-40289-5
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Business and Management
  • Print ISBN 978-3-319-40288-8
  • Online ISBN 978-3-319-40289-5
  • Series Print ISSN 0075-8442
  • Series Online ISSN 2196-9957
  • Buy this book on publisher's site
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