A new optimization algorithm based on a combination of particle swarm optimization, convergence and divergence operators for single-objective and multi-objective problems

Engineering Optimization

Volumn 44, Issue 10, 2012, Pages 1167-1186

  Mahmoodabadi, M J ^a   Bagheri, A ^a   Nariman Zadeh, N ^a,b   Jamali, A ^a  

^a UNIVERSITY OF GUILAN   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

Author keywords

convergence and divergence operators; leader selection method; multi objective optimization; particle swarm optimization; vehicle vibration model

Indexed keywords

BENCHMARK FUNCTIONS; COMPUTATIONAL TIME; CONVERGENCE SPEED; DIVERGENCE OPERATORS; ELIMINATION METHOD; HUMAN SOCIAL INTERACTIONS; MULTI OBJECTIVE; MULTI OBJECTIVE ALGORITHM; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; MULTI OBJECTIVE OPTIMIZATIONS (MOO); MULTI-OBJECTIVE PROBLEM; NONDOMINATED SOLUTIONS; NSGA-II; OBJECTIVE FUNCTIONS; OPTIMIZATION ALGORITHMS; PARETO OPTIMAL SOLUTIONS; PARETO-OPTIMAL DESIGN; POPULATION-BASED OPTIMIZATION METHODS; RELATIVE DISPLACEMENT; SELECTION METHODS; SOLUTION ACCURACY; SPRUNG MASS; TEST FUNCTIONS; TWO-DEGREE OF FREEDOM; VEHICLE VIBRATIONS;

ALGORITHMS; BENCHMARKING; MULTIOBJECTIVE OPTIMIZATION; OPTIMAL SYSTEMS; PARTICLE SWARM OPTIMIZATION (PSO); VIBRATION ANALYSIS;

ITERATIVE METHODS;

EID: 84866668233     PISSN: 0305215X     EISSN: 10290273     Source Type: Journal    
DOI: 10.1080/0305215X.2011.644545     Document Type: Article

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