Titlebook: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems; M.C. Bhuvaneswari Book 2015 Springer

AVERT

Tania Pietrzak,Evelyn Beverly Jahnthe partitions can be minimized and the cells are evenly distributed across the layout surface. MCNC benchmark circuits are used to validate the performance of the multi-objective evolutionary algorithms.

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ms (GA) and particle swarm optimization (PSO).Analyzes experThis book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

JAMB

s and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.978-81-322-3539-2978-81-322-1958-3

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