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Andean Condor Algorithm for cell formation problems

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Abstract

This paper proposes a novel population based optimization algorithm called Andean Condor Algorithm (ACA) for solving cell formation problems. The ACA metaheuristic is inspired by the movement pattern of the Andean Condor when it searches for food. This pattern of movement corresponds to the flight distance traveled by the Andean Condor from its nest to the place where food is found. This distance varies depending on the seasons of the year. The ACA metaheuristic presents a balance of its population through a performance indicator based on the average quality of the population’s fitness. This balance determines the number of Andean Condors that will perform an exploration or intensification movements. ACA metaheuristics have a flexible design. It allows to easily integrate specific heuristics according to the optimization problem to be solved. Two types of computational experiments have been performed. According to the results obtained it has been possible to determine that ACA is an algorithm with an outstanding RPD% in relation to the algorithms BAT, MBO and PSO, robust and with a convergence which tends not to be trapped in the local optimums. Besides, according to the non-parametric multiple comparison, results have been obtained in which the ACA metaheuristic has significant differences in relation to the BAT, MBO and PSO algorithms.

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Acknowledgements

Boris Almonacid is supported by Animal Behavior Society, USA (Developing Nations Research Awards 2016); by Postgraduate Grant Pontificia Universidad Católica de Valparaíso, Chile (VRIEA 2016 and INF-PUCV 2015) and by Ph.D (h.c) Sonia Alvarez, Chile. Ricardo Soto is supported by Grant CONICYT / FONDECYT / REGULAR / 1160455. Also, we thank the anonymous reviewers for their constructive comments.

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    Boris Almonacid & Ricardo Soto

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Correspondence to Boris Almonacid.

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Almonacid, B., Soto, R. Andean Condor Algorithm for cell formation problems. Nat Comput 18, 351–381 (2019). https://doi.org/10.1007/s11047-018-9675-0

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