A shuffled complex evolution algorithm for the multidimensional knapsack problem using core concept

This work addresses the application of a population based evolutionary algorithm called shuffled complex evolution (SCE) in the core of multidimensional knapsack problem (MKP). The core of the MKP is a set of items which are hard to decide if they are or not selected in good solutions. This concept is used to reduce the original size of MKP instances. The performance of the SCE applied to the reduced MKP is verified through computational experiments using well-known instances from literature. The approach proved to be effective in finding near optimal solutions demanding a small amount of processing time.