Titlebook: Massively Parallel Evolutionary Computation on GPGPUs; Shigeyoshi Tsutsui,Pierre Collet Book 2013 Springer-Verlag Berlin Heidelberg 2013 A

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ACO with Tabu Search on GPUs for Fast Solution of the QAPce Architecture (CUDA). In TS on QAPs, there are . neighbors in a candidate solution. These TS moves form two groups based on computing cost. In one group, the computing of the move cost is ., and in the other group the computing of the move cost is .. We compute these groups of moves in parallel by

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New Ideas in Parallel Metaheuristics on GPU: Systolic Genetic Searchnderlying operation relates to systolic computing and is inspired by the systolic contraction of the heart that makes possible blood circulation. The algorithm, called Systolic Genetic Search (SGS), is based on the synchronous circulation of solutions through a grid of processing units and tries to

Isthmus

Cultivate

Morphine

Implementation Techniques for Massively Parallel Multi-objective Optimization as multi-objective optimization (MOO). It has been a challenge for researchers and practitioners to find solutions for MOO problems. Many techniques have been developed in operations research and other related disciplines, but the complexity of MOO problems such as large search spaces, uncertainty,

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Data Mining Using Parallel Multi-objective Evolutionary Algorithms on Graphics Processing Unitso a company under resource constraints. In this chapter, we first formulate this learning problem as a constrained optimization problem and then convert it to an unconstrained multi-objective optimization problem (MOP), which can be handled by some multi-objective evolutionary algorithms (MOEAs). Ho

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Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Unitiple genetic programming (GP) runs on a graphics processing unit (GPU) hardware, each with a population of five million programs both winnows (selects) useful variables from the chaff and evolves small (three inputs) data models. The SPMD CUDA interpreter exploits the GPU’s single instruction multip

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