A self-adaptive harmony search combined with a stochastic local search for the 0-1 multidimensional knapsack problem
Abdellah Rezoug, Dalila Boughaci · International Journal of Bio-Inspired Computation · 2016
This paper presents a new hybrid self-adaptive harmony search combined with a stochastic local search algorithm (SAHS-SLS) to solve the 0-1 multidimensional knapsack problem (MKP). The proposed SAHS-SLS uses SAHS to create harmonies that will be improved with SLS. We propose a dynamic adjustment of the walk probability (wp) in SLS and a technique to compute the bandwidth (bw) and the pitch adjusting rate (PAR) in SAHS. The overall method SAHS-SLS is implemented and evaluated on benchmarks in order to measure its performance in solving the MKP. It is compared to other approaches to show its effectiveness. The numerical results are encouraging and demonstrate the benefit of the proposed approach.