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» On the Brittleness of Evolutionary Algorithms
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GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
15 years 11 months ago
Multicriteria Network Design Using Evolutionary Algorithm
In this paper, we revisit a general class of multi-criteria multi-constrained network design problems and attempt to solve, in a novel way, with Evolutionary Algorithms (EAs). A ma...
Rajeev Kumar, Nilanjan Banerjee
GECCO
2003
Springer
15 years 11 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
EMO
2001
Springer
107views Optimization» more  EMO 2001»
15 years 10 months ago
Multi-objective Optimisation of Cancer Chemotherapy Using Evolutionary Algorithms
The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, t...
Andrei Petrovski, John A. W. McCall
CCGRID
2007
IEEE
15 years 10 months ago
A Hybrid Linear Programming and Evolutionary Algorithm based Approach for On-line Resource Matching in Grid Environments
We describe a hybrid linear programming (LP) and evolutionary algorithm (EA) based resource matcher suitable for heterogeneous grid environments. The hybrid matcher adopts the ite...
Pawel Garbacki, Vijay K. Naik
EVOW
2008
Springer
15 years 7 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