How to solve it: modern heuristics
How to solve it: modern heuristics
An overview of vehicle routing problems
The vehicle routing problem
Tabu Search
A review of metrics on permutations for search landscape analysis
Computers and Operations Research
NILS: a neutrality-based iterated local search and its application to flowshop scheduling
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
On the neutrality of flowshop scheduling fitness landscapes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
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Landscape analysis has been identified as a promising way to develop efficient optimization methods. Nevertheless, the links between properties of the landscape and efficiency of methods is not easy to understand. In this article, we propose to give a contribution in this field using a vehicle routing problem as an illustration. Metaheuristics use a neighborhood operator that connects solutions of the search space. Thus, this operator acts on the dynamics of the search and impacts metaheuristics efficiency. Therefore, we characterize two landscapes differenciated by their neighborhood function and then, we analyze the performance of classical metaheuristics using one or the other neighborhood operator. Finally, a discussion provides insights on the relations between results of the landscape analysis and results of methods performance.