Towards a characterisation of the behaviour of stochastic local search algorithms for SAT
Artificial Intelligence
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Tabu Search for a Network Loading Problem with Multiple Facilities
Journal of Heuristics
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
INFORMS Journal on Computing
Grasp and Path Relinking for 2-Layer Straight Line Crossing Minimization
INFORMS Journal on Computing
Adaptive and Resource-Aware Mining of Frequent Sets
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Networks
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Metaheuristics for optimization problems in computer communications
Computer Communications
Efficient parallel cooperative implementations of GRASP heuristics
Parallel Computing
On the Use of Run Time Distributions to Evaluate and Compare Stochastic Local Search Algorithms
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Handbook of Metaheuristics
Revised GRASP with path-relinking for the linear ordering problem
Journal of Combinatorial Optimization
A hybrid GRASP with data mining for the maximum diversity problem
HM'05 Proceedings of the Second international conference on Hybrid Metaheuristics
A probabilistic heuristic for a computationally difficult set covering problem
Operations Research Letters
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The exploration of hybrid metaheuristics-combination of metaheuristics with concepts and processes from other research areas-has been an important trend in combinatorial optimization research. An instance of this study is the hybrid version of the GRASP metaheuristic that incorporates a data mining process. Traditional GRASP is an iterative metaheuristic which returns the best solution reached over all iterations. In the hybrid GRASP proposal, after executing a significant number of iterations, the data mining process extracts patterns from an elite set of sub-optimal solutions for the optimization problem. These patterns present characteristics of near optimal solutions and can be used to guide the following GRASP iterations in the search through the combinatorial solution space. The hybrid data mining GRASP has been successfully applied for different combinatorial problems: the set packing problem, the maximum diversity problem, the server replication for reliable multicast problem and the p-median problem. In this work, we show that, not only the traditional GRASP, but also GRASP improved with the path-relinking heuristic-a memory-based intensification strategy-could benefit from exploring a data mining procedure. Computational experiments, comparing traditional GRASP with path-relinking and different path-relinking hybrid proposals, showed that employing the combination of path-relinking and data mining made the GRASP find better results in less computational time. Another contribution of this work is the application of the path-relinking hybrid proposal for the 2-path network design problem, which improved the state-of-the-art solutions for this problem.