Fitness landscape of the cellular automata majority problem: View from the "Olympus"
Theoretical Computer Science
On the neutrality of flowshop scheduling fitness landscapes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
The road to VEGAS: guiding the search over neutral networks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
On the neutrality of flowshop scheduling fitness landscapes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Fitness Landscape Analysis and Metaheuristics Efficiency
Journal of Mathematical Modelling and Algorithms
Fitness landscapes and graphs: multimodularity, ruggedness and neutrality
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
ParadisEO-MO: from fitness landscape analysis to efficient local search algorithms
Journal of Heuristics
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This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals with the fact that the same fitness value is assigned to numerous solutions from the search space. Many combinatorial optimization problems share this property, that is generally very inhibiting for local search algorithms. A neutrality-based iterated local search, that allows neutral walks to move on the plateaus, is proposed and experimented on a permutation flowshop scheduling problem with the aim of minimizing the makespan. Our experiments show that the proposed approach is able to find improving solutions compared with a classical iterated local search. Moreover, the tradeoff between the exploitation of neutrality and the exploration of new parts of the search space is deeply analyzed.