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A Percentile Transition Ranking Algorithm Applied to Knapsack Problem

2017; Springer Nature; Linguagem: Inglês

10.1007/978-3-319-67621-0_11

2194-5357

José García, Broderick Crawford, Ricardo Soto, Gino Astorga,

Optimization and Packing Problems

The binarization of Swarm Intelligence continuous metaheuristics is an area of great interest in operational research. This interest is mainly due to the application of binarized metaheuristics to combinatorial problems. In this article we propose a general binarization algorithm called Percentile Transition Ranking Algorithm (PTRA). PTRA uses the percentile concept as a binarization mechanism. In particular we will apply this mechanism to the Cuckoo Search metaheuristic to solve the set multidimensional Knapsack problem (MKP). We provide necessary experiments to investigate the role of key ingredients of the algorithm. Finally to demonstrate the efficiency of our proposal, we solve Knapsack benchmark instances of the literature. These instances show PTRA competes with the state-of-the-art algorithms.