Proceedings ArticleDOI
Multiplicity and local search in evolutionary algorithms to build the Pareto front
H.A. Leiva,S.C. Esquivel,Raúl Hector Gallard +2 more
- pp 7-13
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TLDR
The present proposal incorporates a hybridisation of global and local search to the multiplicity approach and combines the evolutionary approach combined with simulated annealing and neighbourhood search to produce better results.Abstract:
In multicriteria optimization determination of the Pareto-optimal front is of utmost importance for decision making. Simultaneous parallel search for multiple members of an evolutionary algorithm can lead to effective optimization. In a previous approach (Esquivel et al., 1999) extending the ideas of a former work of (Lis and Eiben, 1997), we proposed the multi-sexual-parents-crossovers genetic algorithm (MSPC-GA), a method which by allowing multiple parents per sex and multiple crossovers per mating action attempted to balance the explorative and exploitative efforts which are present in any evolutionary algorithm. The performance of the method produced an evenly distributed and larger set of efficient points. Following this concept the present proposal incorporates a hybridisation of global and local search to the multiplicity approach. Now the evolutionary approach combined with simulated annealing and neighbourhood search produced better results.read more
Citations
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Journal ArticleDOI
Improving convergence of evolutionary multi-objective optimization with local search: a concurrent-hybrid algorithm
TL;DR: Simulation results of the new concurrent-hybrid algorithm on several two to four-objective problems compared to a serial approach, clearly show the importance of local search in aiding a computationally faster and accurate convergence to the Pareto optimal front.
Journal ArticleDOI
Multi-Objective tool to optimize the Water Resources Management using Genetic Algorithm and the Pareto Optimality Concept
TL;DR: In this paper, the authors examined the development of a multi-objective tool, called "ALL_WATER", in optimizing water resources management, where the objectives of satisfying demand and reducing costs were taken into consideration while at the same time respecting water salinity requirements and hydraulic constraints.
Journal ArticleDOI
Multi-objective Optimization Tool for Integrated Groundwater Management
TL;DR: In this paper, a tool called ALL_WATER_gw was developed for groundwater management within the framework of the WEAP-MODFLOW Decision Support System, which takes into account satisfaction of demand, minimization of water cost and maximal drawdown, as well as meeting water salinity restrictions.
Journal Article
A Web-Mining Approach to Disambiguate Biomedical Acronym Expansions
Mathieu Roche,Violaine Prince +1 more
TL;DR: Nine quality measures of the relevant definition prediction based on mutual information (MI), cubic MI (MI3), and Dice’s coefficient are provided and a combinaison of these statistical measures with the cosine approach is proposed.
Journal ArticleDOI
A Hybrid Multi‐Objective Evolutionary Algorithm for Optimal Groundwater Management under Variable Density Conditions
TL;DR: In this paper, a hybrid MOEA, the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), is proposed for the management of groundwater resources under variable density conditions.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Muiltiobjective optimization using nondominated sorting in genetic algorithms
N. Srinivas,Kalyanmoy Deb +1 more
TL;DR: Goldberg's notion of nondominated sorting in GAs along with a niche and speciation method to find multiple Pareto-optimal points simultaneously are investigated and suggested to be extended to higher dimensional and more difficult multiobjective problems.
Book
Handbook of Evolutionary Computation
TL;DR: The Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications, intended to become the standard reference resource for the evolutionary computation community.
Journal ArticleDOI
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
TL;DR: The problem features that may cause a multi-objective genetic algorithm (GA) difficulty in converging to the true Pareto-optimal front are studied to enable researchers to test their algorithms for specific aspects of multi- objective optimization.
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