abstract
- © 2018, Springer International Publishing AG, part of Springer Nature. The knapsack problem is a fundamental problem that has been extensively studied in combinatorial optimization. The reason is that such a problem has many practical applications. Several solution techniques have been proposed in the past, but their performance is usually limited by the complexity of the problem. Hence, this paper studies a novel hyper-heuristic approach based on the ant colony optimization algorithm to solve the knapsack problem. The hyper-heuristic is used to produce rules that decide which heuristic to apply given the current problem state of the instance being solved. We test the hyper-heuristic model on sets with a variety of knapsack problem instances. Our resulting data seems promising.