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Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems

  • Son Duy Dao

Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Son Duy Dao
    Pages 1-7
  3. Son Duy Dao
    Pages 9-33
  4. Son Duy Dao
    Pages 89-140
  5. Back Matter
    Pages 147-147

About this book

Introduction

This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.

Keywords

VCIM Production Scheduling Model Collaborative Shipment Scheduling Partner Selection Multiple Product Orders Multiple Objective Functions Stochastic Model Genetic Algorithm Unique Chromosome Encoding Innovative Algorithm Structure Adaptive Stop-and-Restart-with-Memory Mechanism

Authors and affiliations

  • Son Duy Dao
    • 1
  1. 1.School of EngineeringUniversity of South AustraliaAdelaideAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-72113-2
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-72112-5
  • Online ISBN 978-3-319-72113-2
  • Series Print ISSN 2190-5053
  • Series Online ISSN 2190-5061
  • Buy this book on publisher's site