Open AccessJournal Article
Evolving objects: A general purpose evolutionary computation library
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TL;DR: What features an object must have in order to evolve is described, and some examples of how EO has been put to practice evolving neural networks, solutions to the Mastermind game, and other novel applications are described.
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Abstract: This paper presents the evolving objects library (EOlib), an object-oriented framework for evolutionary computation (EC) that aims to provide a flexible set of classes to build EC applications. EOlib design objective is to be able to evolve any object in which fitness makes sense. In order to do so, EO concentrates on interfaces; any object can evolve if it is endowed with an interface to do so. In this paper, we describe what features an object must have in order to evolve, and some examples of how EO has been put to practice evolving neural networks, solutions to the Mastermind game, and other novel applications.
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Citations
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Combinatorial optimization of stochastic multi-objective problems: an application to the flow-shop scheduling problem
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TL;DR: In this paper, a proactive stochastic approach where processing times are represented by random variables is presented and several multi-objective methods that are able to handle any type of probability distribution are proposed.
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Algorithm::Evolutionary, a flexible Perl module for evolutionary computation
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- 01 Aug 2010
TL;DR: Algorithm::Evolutionary (A::E), a Perl module released under an open source license and designed for the exploration and exploitation of evolutionary algorithms, is described and the myth of low performance of scripting languages is tried to dispel.
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A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
Kalyanmoy Deb,Samir Agrawal,Amrit Pratap,T. Meyarivan +3 more
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TL;DR: Simulation results on five difficult test problems show that the proposed NSGA-II, in most problems, is able to find much better spread of solutions and better convergence near the true Pareto-optimal front compared to PAES and SPEA--two other elitist multi-objective EAs which pay special attention towards creating a diverse Paretimal front.
Evolutionary algorithms for constrained parameter optimization problems
TL;DR: Difficulty connected with solving the general nonlinear programming problem is discussed; several approaches that have emerged in the evolutionary computation community are surveyed; and a set of 11 interesting test cases are provided that may serve as a handy reference for future methods.
Your brains and my beauty: parent matching for constrained optimisation
Robert Hinterding,Zbigniew Michalewicz +1 more
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TL;DR: This paper introduces a new element to evolutionary algorithms for constrained parameter optimization problems: the parent matching mechanism and shows that the proposed technique works very well on selected test cases.
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TL;DR: First, considering the measure given by the density of 1's, the Uniform Covering initialization procedure is naturally designed, and second, taking into account the probability of appearance of sequences of identical bits leads to design another alternative initialization procedure, the Homogeneous Block procedure.
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