In this paper we present a new memetic approach to solve the orienteering problem. The key method of our proposal is the procedure ReduceExtend which, starting from a permutation of all the vertices in the orienteering problem, produces a feasible path with a locally optimal score. This procedure is coupled with an evolutionary algorithm which navigate the search space of permutations. In our experiments we have considered the following algorithms: the algebraic differential evolution algorithm, and the three continuous algorithms CMA-ES, DE and PSO equipped with the random key technique. The experimental results show that the proposed approach is competitive with the state of the art results of some selected benchmark instances.
Titolo: | A Memetic Approach for the Orienteering Problem |
Autori: | |
Data di pubblicazione: | 2020 |
Serie: | |
Handle: | http://hdl.handle.net/20.500.12071/20745 |
ISBN: | 978-3-030-45015-1 978-3-030-45016-8 |
Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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