Advances in Multi-Objective Nature Inspired Computing
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منابع مشابه
An Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distribu...
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1 CINVESTAV-IPN, Departamento de Computación, Av. IPN No. 2508, Col. San Pedro Zacatenco, México, D.F. 07300, Mexico [email protected] 2 Laboratoire d’Informatique Fondamentale de Lille (LIFL), UMR CNRS 8022, Université Lille 1, Bâtiment M3, 59655 Villeneuve d’Ascq cedex, France 3 INRIA Lille-Nord Europe, Parc Scientifique de la Haute Borne, 40 avenue Halley, 59650 Villeneuve d’Ascq, Fran...
متن کاملOptimization of Agricultural BMPs Using a Parallel Computing Based Multi-Objective Optimization Algorithm
Beneficial Management Practices (BMPs) are important measures for reducing agricultural non-point source (NPS) pollution. However, selection of BMPs for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. Due to its iterative nature, the optimization typically takes a long time to achieve the BMP trade-off results which is not desirable ...
متن کاملApproximating Pareto-Optimal Sets Using Diversity Strategies in Evolutionary Multi-Objective Optimization
Often the Pareto front of a multi-objective optimization problem grows exponentially with the problem size. In this case, it is not possible to compute the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such approximations by using different diversity mechanisms. We discuss some well-known approaches such as the d...
متن کاملFuzzy Apriori Rule Extraction Using Multi-Objective Particle Swarm Optimization: The Case of Credit Scoring
There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...
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