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» Removing the Genetics from the Standard Genetic Algorithm
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ESWA
2011
230views Database» more  ESWA 2011»
13 years 3 months ago
Multi-objective genetic algorithms for scheduling of radiotherapy treatments for categorised cancer patients
This paper presents a multi-objective optimisation model and algorithms for scheduling of radiotherapy treatments for categorised cancer patients. The model is developed considerin...
Dobrila Petrovic, Mohammad Morshed, Sanja Petrovic
CEC
2005
IEEE
13 years 10 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
GPEM
2000
121views more  GPEM 2000»
13 years 8 months ago
Bayesian Methods for Efficient Genetic Programming
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Byoung-Tak Zhang
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
13 years 9 months ago
Deriving evaluation metrics for applicability of genetic algorithms to optimization problems
This paper aims to identify the missing links from theory of Genetic Algorithms (GAs) to application of GAs. Categories and Subject Descriptors: J.0 [Computer Applications]: Gener...
Hsinyi Jiang, Carl K. Chang
GECCO
2004
Springer
114views Optimization» more  GECCO 2004»
14 years 2 months ago
Hybrid Genetic Algorithms for Multi-Objective Optimisation of Water Distribution Networks
Abstract. Genetic algorithms have been a standard technique for engineers optimising water distribution networks for some time. However in recent years there has been an increasing...
Ed Keedwell, Soon-Thiam Khu