QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
Measuring the Spatial Dispersion of Evolutionary Search Processes: Application to Walksat
Selected Papers from the 5th European Conference on Artificial Evolution
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Constraint-Based Local Search
A review of metrics on permutations for search landscape analysis
Computers and Operations Research
The structure of local search diversity
Math'04 Proceedings of the 5th WSEAS International Conference on Applied Mathematics
Adaptive operator selection with dynamic multi-armed bandits
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A Compass to Guide Genetic Algorithms
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Reactive Search and Intelligent Optimization
Reactive Search and Intelligent Optimization
Autonomous Control Approach for Local Search
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Hierarchical Iterated Local Search for the Quadratic Assignment Problem
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Search intensity versus search diversity: a false trade off?
Applied Intelligence
Autonomous operator management for evolutionary algorithms
Journal of Heuristics
An exploration-exploitation compromise-based adaptive operator selection for local search
Proceedings of the 14th annual conference on Genetic and evolutionary computation
A comparison of operator utility measures for on-line operator selection in local search
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
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This paper presents a study for the dynamic selection of operators in a local search process. The main purpose is to propose a generic autonomous local search method which manages operator selection from a set of available operators, built on neighborhood relations and neighbor selection functions, using the concept of Pareto dominance with respect to quality and diversity. The latter is measured using two different metrics. This control method is implemented using the Comet language in order to be easily introduced in various constraint local search algorithms. Focusing on permutation-based problems, experimental results are provided for the QAP and ATSP to assess the method's effectiveness.