A quantum artificial bee colony algorithm based on quantum walk for the 0–1 knapsack problem

Abstract Based on the characteristics of the quantum mechanism, a novel quantum walk artificial bee colony algorithm is proposed to promote performance. Firstly, the discrete quantum walk is an approach taken to search for new food sources in the updated phase for employed bees and onlooker bees, which can enhance the probability of the target solution to extend the exploration capability. Secondly, the food source selection policy of the onlooker bees changes, from roulette selection to tournament selection, to boost exploitation and convergence speed. Finally, the novel algorithm is brought forward, along with the approach to analyze 0–1 knapsack problems. The experimental results prove that our algorithm can overcome the premature phenomenon and perform better in the areas of search capability, convergence speed, and stability performance. The performance is superior to that of the conventional artificial bee colony algorithm, as well as the genetic algorithm, in a set of 0–1 knapsack problems.