Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling

Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling

ISBN-10:
3319628925
ISBN-13:
9783319628929
Pub. Date:
08/24/2017
Publisher:
Springer International Publishing
ISBN-10:
3319628925
ISBN-13:
9783319628929
Pub. Date:
08/24/2017
Publisher:
Springer International Publishing
Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling

Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling

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Overview

This book addresses two of the most difficult and computationally intractable classes of problems: discrete resource constrained scheduling, and discrete-continuous scheduling. The first part of the book discusses problems belonging to the first class, while the second part deals with problems belonging to the second class. Both parts together offer valuable insights into the possibility of implementing modern techniques and tools with a view to obtaining high-quality solutions to practical and, at the same time, computationally difficult problems. It offers a valuable source of information for practitioners dealing with the real-world scheduling problems in industry, management and administration.

The authors have been working on the respective problems for the last decade, gaining scientific recognition through publications and active participation in the international scientific conferences, and their results are obtained using population-based methods. Dr E. Ratajczk-Ropel explores multiple agent and A-Team concepts, while Dr A. Skakovski focuses on evolutionary algorithms with a particular focus on the population learning paradigm.


Product Details

ISBN-13: 9783319628929
Publisher: Springer International Publishing
Publication date: 08/24/2017
Series: Studies in Systems, Decision and Control , #108
Edition description: 1st ed. 2018
Pages: 236
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

Introduction.- Agent-Based Optimization.- Project Scheduling Models.- Multi-Mode Resource-Constrained Project Scheduling.- State of the Art Review.- Performance Evaluation of the Proposed Algorithms.- Conclusions.

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