A multilevel algorithm for large unconstrained binary quadratic optimization
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Memetic search for the max-bisection problem
Computers and Operations Research
Breakout Local Search for maximum clique problems
Computers and Operations Research
A memetic approach for the max-cut problem
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Combinatorial complexity problem reduction by the use of artificial vaccines
Expert Systems with Applications: An International Journal
Breakout local search for the vertex separator problem
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Graph partitioning is one of the most studied NP-complete problems. Given a graph $G=(V, E)$ , the task is to partition the vertex set $V$ into $k$ disjoint subsets of about the same size, such that the number of edges with endpoints in different subsets is minimized. In this paper, we present a highly effective multilevel memetic algorithm, which integrates a new multiparent crossover operator and a powerful perturbation-based tabu search algorithm. The proposed crossover operator tends to preserve the backbone with respect to a certain number of parent individuals, i.e., the grouping of vertices which is common to all parent individuals. Extensive experimental studies on numerous benchmark instances from the graph partitioning archive show that the proposed approach, within a time limit ranging from several minutes to several hours, performs far better than any of the existing graph partitioning algorithms in terms of solution quality.