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Multi Knapsack Problem (MKP) is NP-hard combinational optimization problem, also known as the multi-constraint knapsack problem. MKP is one of the most studied problems in combinatorial optimization, with variety of real-life applications. In this paper a Stochastic Diffusion Binary differential evolution (SD-BDE) algorithm is applied for optimizing the Multidimensional Knapsack Problem (MKP). SD-BDE, is a Binary version of Differential Evolution hybridized with ideas extracted from Stochastic Diffusion search. SD-BDE algorithm, in this paper, is compared against state-of-the-art existing algorithms in solving MKP. Experimental results show that the SD-BDE algorithm outperformed the existing algorithms by finding either better or at least similar solutions for all tested benchmarks

Stochastic Diffusion Binary Differential Evolution to Solve Multidimensional Knapsack Problem