2011 · 13 citations · 8 references
Natural SciencesMathematicsDesign OptimizationOptimizationParallel AlgorithmsCombinatorial OptimizationCrossover OperatorsEvolutionary ComputationGenetic AlgorithmsMetaheuristic OptimizationPopulation-based SearchEvolutionary AlgorithmsGenetic Algorithms For SearchHybrid Evolutionary AlgorithmsKnapsack ProblemsParticle Swarm OptimizationSolution Quality Assessment
paper, a modified hybrid Particle Swarm Optimization (MHPSO) algorithm that combines some principles of Particle Swarm Optimization (PSO) and Crossover operation of the Genetic Algorithm (GA) is presented. Our contribution has a twofold aim: first, is to propose a new hybrid PSO algorithm. Second is to prove the effectiveness of the proposed algorithm in dealing with NP-hard and combinatorial optimization problems. In order to test and validate our algorithm, we have used it for solving the Multidimensional Knapsack Problem (MKP) which is a NP-hard combinatorial optimization problem. The experimental results based on some benchmarks from OR-Library, show a good and promise solution quality obtained by the proposed algorithm.
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James Kennedy, R.C. Eberhart · 2002 · 47.5K citations
A discrete binary version of the particle swarm algorithm
James Kennedy, R.C. Eberhart · 2002 · 4.7K citations
A Genetic Algorithm for the Multidimensional Knapsack Problem
P.C. Chu, J. E. Beasley · Journal of Heuristics · 1998 · 816 citations
Where are the hard knapsack problems?
David Pisinger · Computers & Operations Research · 2004 · 412 citations