Journal Article10.1016/J.AMC.2006.09.010
A particle gradient evolutionary algorithm for solving multi-objective problems
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TL;DR: The experiments show that this algorithm cannot only converge to the global Pareto optimal front quickly, uniformly, and precisely, but also can avoid the premature phenomenon of multi-objective problems.
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About: This article is published in Applied Mathematics and Computation. The article was published on 01 Apr 2007. The article focuses on the topics: Multi-objective optimization & Evolutionary algorithm.
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Citations
A hybrid shuffled complex evolution approach based on differential evolution for unconstrained optimization
Viviana Cocco Mariani,Viviana Cocco Mariani,Luiz Guilherme Justi Luvizotto,Fabio Alessandro Guerra,Fabio Alessandro Guerra,Leandro dos Santos Coelho,Leandro dos Santos Coelho +6 more
TL;DR: A metaheuristic algorithm called Modified Shuffled Complex Evolution (MSCE) is proposed, where an adaptation of the Downhill Simplex search strategy combined with the differential evolution method is proposed.
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TL;DR: In the paper, particle gradient multi-objective evolutionary algorithm (PGMOEA) on GPU is presented and it is demonstrated that PGMOEA onGPU is much more effective and efficient than PG MOEA on CPU.
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- 30 Dec 2008
TL;DR: This paper presents a novel evolutionary algorithm for dynamic risk grading of major hazards, which can be called DRGEA for short, and details the construction theory from many aspects such as individual encoding, evolutionary operators, fitness function and so forth.
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Stream Cipher Generation Method Based on Particle Gradient Multi-objective Evolutionary Algorithm
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