Paper Info
Title
Analysis And Efficiency Of Randomized Optimization Heuristics
Abstract
Problems of global optimization arise inmany areas of modern science and have an ample number of applications in engineering, industry and economics as for circuit design, process planning, and scheduling. There are various heuristic methods to solve these problems such as bio-inspired approaches like Evolutionary Algorithms or Particle Swarm Optimization but also simpler approaches as Simulated Annealing or Threshold Accepting. In this article we introduce new analytical approaches to understand the underlying principles in particular of parallel evolutionary methods and their parameters better. More specific, we focus on the benefit of migration in the island model of evolutionary algorithms and on the influence of migration parameters.
Year
DOI
Venue
2010
10.1524/itit.2010.0613
IT-INFORMATION TECHNOLOGY
Field
DocType
Volume
Computer science,Theoretical computer science,Heuristics,Theory of computation,Embedded system
Journal
52
Issue
ISSN
Citations 
6
1611-2776
0
PageRank 
References 
Authors
0.34
3
1
Name
Order
Citations
PageRank
Jörg Lässig117522.53