Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6896848 | European Journal of Operational Research | 2015 | 10 Pages |
Abstract
The Standard Quadratic Problem (StQP) is an NP-hard problem with many local minimizers (stationary points). In the literature, heuristics based on unconstrained continuous non-convex formulations have been proposed (Bomze & Palagi, 2005; Bomze, Grippo, & Palagi, 2012) but none dominates the other in terms of best value found. Following (Cassioli, DiLorenzo, Locatelli, Schoen, & Sciandrone, 2012) we propose to use Support Vector Machines (SVMs) to define a multistart global strategy which selects the “best” heuristic. We test our method on StQP arising from the Maximum Clique Problem on a graph which is a challenging combinatorial problem. We use as benchmark the clique problems in the DIMACS challenge.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Umberto Dellepiane, Laura Palagi,