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EVOW
2008
Springer
15 years 4 months ago
A Memory Enhanced Evolutionary Algorithm for Dynamic Scheduling Problems
Abstract. This paper describes a memory enhanced evolutionary algorithm (EA) approach to the dynamic job shop scheduling problem. Memory enhanced EAs have been widely investigated ...
Gregory J. Barlow, Stephen F. Smith
106
Voted
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 8 months ago
Diversity as a selection pressure in dynamic environments
Evolutionary algorithms (EAs) are widely used to deal with optimization problems in dynamic environments (DE) [3]. When using EAs to solve DE problems, we are usually interested i...
Lam Thu Bui, Jürgen Branke, Hussein A. Abbass
GECCO
2003
Springer
15 years 7 months ago
The State Problem for Evolutionary Testing
Abstract. This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is re...
Phil McMinn, Mike Holcombe
135
Voted
ICAI
2003
15 years 4 months ago
Exploiting the Marginal Profits of Constraints with Evolutionary Multi-Objective Optimization Techniques
Many real-world search and optimization problems naturally involve constraint handling. Recently, quite a few heuristic methods were proposed to solve the nonlinear constrained op...
Zhenyu Yan, Wei Zhi, Lishan Kang
114
Voted
SAC
2004
ACM
15 years 8 months ago
A comparison of randomized and evolutionary approaches for optimizing base station site selection
It is increasingly important to optimally select base stations in the design of cellular networks, as customers demand cheaper and better wireless services. From a set of potentia...
Larry Raisanen, Roger M. Whitaker, Steve Hurley