Results 11 to 20 of about 4,528,698 (293)
PDGA: The primal-dual genetic algorithm [PDF]
, 2003 Copyright @ 2003 IOS PressGenetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the performance of GAs.
Yang, S
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PGGA: A predictable and grouped genetic algorithm for job scheduling [PDF]
, 2006 This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimation algorithm is designed to estimate a job workload based on its historical execution records, (2 ...
Li, M, Qi, M, Yu, B
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3D freeform component fixture design optisation using a genetic algorithm [PDF]
, 2007 This paper details an application of genetic algorithms (GA) developed for the optimisation of fixture locator positioning for 3D freeform components. Based on the information of the workpiece, a genetic algorithm based approach is applied to determine ...
Chen, Xun, Yeung, Ka Yiu
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A Novel Genetic Operator for Genetic Folding Algorithm: A Refolding Operator and A New Genotype [PDF]
, 2017 Genetic Folding algorithm uses linear chromosomes composed of organized genes in floating-numbers manner in which each genes chain fold back on themselves to form the final GF chromosome. In this paper, a novel genotype representation and a novel genetic
Mohammd A. Mezher +4 more
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SLA based cloud service composition using genetic algorithm [PDF]
, 2016 Cloud computing tends to provide high quality on-demand services to the users. Numerous services are evolving today. Functionally similar services are having different non-functional properties such as reliability, availability, accessibility, response ...
N Sasikaladevi, Sasikaladevi, N
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A guided search genetic algorithm for the university course timetabling problem [PDF]
, 2009 Copyright @ 2009 MISTAThe university course timetabling problem is a combinatorial optimisation problem in which a set of events has to be scheduled in time slots and located in suitable rooms. The design of course timetables for academic institutions is
Yang, S, Jat, SN
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CoRR, 2021 Death has long been overlooked in evolutionary algorithms. Recent research has shown that death (when applied properly) can benefit the overall fitness of a population and can outperform sub-sections of a population that are "immortal" when allowed to evolve together in an environment [1].
Micah Burkhardt, Roman V. Yampolskiy
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Proposed Genetic Classification Algorithm
Revista Cubana de Ingeniería, 2013 The extraction of knowledge is the basis for decision making in various processes, data mining beingan area of fundamental knowledge to attain that end.
José Leandro González González +1 more
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CROSSOVER OPERATORS IN GENETIC ALGORITHMS: A REVIEW [PDF]
ICTACT Journal on Soft Computing, 2015 The performance of Genetic Algorithm (GA) depends on various operators. Crossover operator is one of them. Crossover operators are mainly classified as application dependent crossover operators and application independent crossover operators.
A.J. Umbarkar, P.D. Sheth
doaj
A Hybrid Genetic-Hierarchical Algorithm for the Quadratic Assignment Problem
Entropy, 2021 In this paper, we present a hybrid genetic-hierarchical algorithm for the solution of the quadratic assignment problem. The main distinguishing aspect of the proposed algorithm is that this is an innovative hybrid genetic algorithm with the original ...
Alfonsas Misevičius, Dovilė Verenė
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