A New Hybrid Binary Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem
作者： Amira Gherboudj , Said Labed , Salim Chikhi
DOI: 10.1007/978-3-642-30157-5_49
关键词:
摘要: In this paper, we presented a New Hybrid Binary Particle Swarm Optimization (NHBPSO). This hybridization consists at combining some principles of (PSO) and Crossover Operation the Genetic Algorithm (GA). The proposed algorithm is used to solving NP-hard combinatorial optimization problem Multidimensional Knapsack Problem (MKP). aim access efficiency performance our NHBPSO have tested it on benchmarks from OR-Library compared results with obtained by standard binary penalty function technique (PSO-P) quantum version (QICSA) new metaheuristic Cuckoo Search. experimental show good promise solution quality which outperforms PSO-P QICSA algorithms.
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