A Binary Ant Lion Optimizer applied to Knapsack problem

摘要

Combinatorial problems with NP-hard complexity appear frequently in operational research. Making robust algorithms that solve these combinatorial problems is of interest in operational research. In this article, a binarization mechanism is proposed so that continuous metaheuristics can solve combinatorial problems. The binarization mechanism uses the concept of percentile. This percentile mechanism is applied to the ant lion algorithm. The NP-hard knapsack problem (MKP) was used to verify our algorithm. Additionally, the binary percentile algorithm was compared with other algorithms that have recently has solved the MKP, observing that the percentile algorithm produces competitive results.