A Binary Multi-Scale Quantum Harmonic Oscillator Algorithm for 0–1 Knapsack Problem With Genetic Operator

摘要: The 0–1 knapsack problem is a typical discrete combinatorial optimization with numerous applications. In this paper, binary multi-scale quantum harmonic oscillator algorithm (BMQHOA) genetic operator proposed for solving problem. framework of BMQHOA consisted three nested phases including energy level stablization, decline and scale adjustment. BMQHOA, the number different bits between solutions defined as distance to map continuous search space into space. Repair greedy strategy adopted in guarantee capacity constraint. current best solution used perform random mutation origin solutions, making evolve towards optimal solution. performance evaluated on two low-dimensional high-dimensional KP01 data sets, computational results are compared several state-of-art algorithms. Experimental demonstrate that can get most performs well convergence stability.