0000000000013058

AUTHOR

Yew-soon Ong

0000-0002-4480-169x

showing 2 related works from this author

An adaptive multimeme algorithm for designing HIV multidrug therapies.

2007

This paper proposes a period representation for modeling the multidrug HIV therapies and an Adaptive Multimeme Algorithm (AMmA) for designing the optimal therapy. The period representation offers benefits in terms of flexibility and reduction in dimensionality compared to the binary representation. The AMmA is a memetic algorithm which employs a list of three local searchers adaptively activated by an evolutionary framework. These local searchers, having different features according to the exploration logic and the pivot rule, have the role of exploring the decision space from different and complementary perspectives and, thus, assisting the standard evolutionary operators in the optimizati…

ScheduleMathematical optimizationComputer scienceAnti-HIV AgentsHIV therapy designAdaptive algorithms; HIV therapy design; Memetic algorithms; Nonlinear integer programming; Algorithms; Anti-HIV Agents; Biomimetics; Computer Simulation; Drug Combinations; Drug Design; Drug Therapy Computer-Assisted; HIV Infections; Humans; Immunity Innate; Models ImmunologicalHIV InfectionsReduction (complexity)Computer-AssistedDrug TherapyModelsBiomimeticsGeneticsInnateHumansComputer SimulationRepresentation (mathematics)MetaheuristicStatistical hypothesis testingFlexibility (engineering)Applied MathematicsNonlinear integer programmingImmunityModels ImmunologicalAdaptive algorithmsImmunity InnateDrug Therapy Computer-AssistedDrug CombinationsImmunologicalDrug DesignMemetic algorithmsMemetic algorithmAlgorithmAlgorithmsBiotechnologyPremature convergenceIEEE/ACM transactions on computational biology and bioinformatics
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Ockham's Razor in Memetic Computing: Three Stage Optimal Memetic Exploration

2012

Memetic computing is a subject in computer science which considers complex structures as the combination of simple agents, memes, whose evolutionary interactions lead to intelligent structures capable of problem-solving. This paper focuses on memetic computing optimization algorithms and proposes a counter-tendency approach for algorithmic design. Research in the field tends to go in the direction of improving existing algorithms by combining different methods or through the formulation of more complicated structures. Contrary to this trend, we instead focus on simplicity, proposing a structurally simple algorithm with emphasis on processing only one solution at a time. The proposed algorit…

FOS: Computer and information sciencesComputer Science - Machine LearningInformation Systems and ManagementComputer scienceComputer Science - Artificial Intelligencemedia_common.quotation_subjectEvolutionary algorithmComputational intelligenceField (computer science)Theoretical Computer ScienceMachine Learning (cs.LG)Artificial IntelligenceSimplicitymemetic algorithmsevolutionary algorithmsmedia_common:Engineering::Computer science and engineering [DRNTU]business.industrycomputational intelligence optimizationComputer Science ApplicationsArtificial Intelligence (cs.AI)Control and Systems Engineeringmemetic computing:Engineering::Electrical and electronic engineering [DRNTU]Memetic algorithmAlgorithm designArtificial intelligencebusinessSoftware
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