A Developmental Evolutionary Algorithm for 0-1 Knapsack Problem

In this paper, a developmental evolutionary algorithm (DEA) is proposed, which mainly based on the developmental evolutionary and learning theory. We regarded the chromosome individual that in EC as an autonomous development individual; and developed mental capabilities through autonomous real-time interactions with its environments by using development learning methods under the control of its intrinsic developmental program, when chromosome individual achieved the development objective, genetic operation started immediately, otherwise continue developing. Finally, we used DEA to solve the 0/1 knapsack problem and designed experiment to compare with QEA, ACO. Experimental results showed that DEA has better convergence, and can effectively avoid falling into local optimal solution.