GA‐Based Multi‐Objective Optimization for Retrofit Design on a Multi‐Core PC Cluster

Abstract

This article presents a distributed nondominated sorting genetic algorithm II (NSGA-II

New discrete-time robust H2/H∞ algorithm for vibration control of smart structures using linear matrix inequalities

“…A related frontier of structural engineering research is health monitoring of structures where significant advances have been made in recent years (Su et al, 2014;O'Byrne et al, 2014;Park et al, 2015). For example, Cha and Buyukozturk (2015) present structural damage detection using modal strain energy and a multi-objective genetic algorithm for optimization (Jia et al, 2014;Luna et al, 2014;Paris et al, 2015).…”

Physics‐based search and optimization: Inspirations from nature

“…where x i ( t ) represents a candidate solution at iteration t , f i is the fitness function value of x i ( t ), and N is the population size. This operator is different from selection operator used in many other optimization algorithms such as genetic algorithms (GA); (Lee, & Arditi, ; Paris, Pedrino, & Nicoletti, ; Bolourchi, Masri, & Aldraihem, ; Park, Oh, & Park, ), genetic programming (Rashidi & Ranjitkar, ; Mesejo et al, ), or particle swarm optimization (PSO) (Zeng, Xu, Wu, & Shen, ; Shabbir & Omenzetter, ).…”

Meta‐heuristic multi‐ and many‐objective optimization techniques for solution of machine learning problems

“…In recent years, considerable attention has been devoted to meta‐heuristic methodologies based on social dynamics and/or the behaviour of live beings and inspired by nature (N. Siddique & Adeli, ; N. H. Siddique & Adeli, ). Among the most widely used techniques mentioned in this review are genetic algorithms (Mencıa, Sierra, Mencıa, & Varela, ; Paris, Pedrino, & Nicoletti, ; Park, Oh, & Park, ; Pillon, Pedrino, Roda, & Nicoletti, ), particle swarm otimization (Alexandridis, Paizis, Chondrodima, & Aliaj, ; Boulkabeit, Mthembu, De Lima Neto, & Marwala, ; Shabbir & Omenzetter, ), the harmony search algorithm (N. H. Siddique & Adeli, , ant colony optimization (Dorigo & Di Caro, ), artificial bee colony (Karaboga & Basturk, ), artificial immune systems (de Castro & Timmis, ), genetic programming (Koza, ), tabu search (Gómez, Pacheco, & Gonzalo‐Orden, ), and physics‐based algorithms (N. H. Siddique & Adeli, ) such as the gravitational search algorithm (N. H. Siddique & Adeli, ).…”