Design and Analysis of Evolutionary Algorithms for the No-wait Flow-shop Scheduling Problem

Jens Czogalla () and Andreas Fink
Additional contact information
Jens Czogalla: Helmut-Schmidt-University/UniBw Hamburg
Andreas Fink: Helmut-Schmidt-University/UniBw Hamburg

Chapter 7 in Metaheuristics in the Service Industry, 2009, pp 99-126 from Springer

Abstract: Abstract Evolutionary algorithms are generally based on populations of solutions which are subject to the application of operators such as recombination, mutation, and selection in order to evolve the population and eventually obtain high-quality solutions. Different, yet often similar evolutionary algorithms are discussed in various research communities from different perspectives. In this work we strive for a better understanding of the performance of different designs within the general framework of evolutionary computation. We examine and compare (discrete) particle swarm optimization with classic genetic algorithms, both with and without hybridization with local search. In particular, we analyze the effect of different selection and reproduction mechanisms on solution quality, population diversity, and convergence behavior, and examine approaches for maintaining population diversity. As application we consider an NP-hard combinatorial optimization problem, namely the no-wait (continuous) flow-shop scheduling problem with flow-time criterion. The computational results support the importance of local search within (hybridized) evolutionary algorithms and show how solution quality depends on a reasonable design of crossover operators, distance functions, population diversity measures, and the control of population diversity.

Keywords: Particle Swarm Optimization; Schedule Problem; Local Search; Crossover Operator; Memetic Algorithm (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-00939-6_7

Ordering information: This item can be ordered from
http://www.springer.com/9783642009396

DOI: 10.1007/978-3-642-00939-6_7

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().