Dynamic Local Search for the Maximum Clique Problem
نویسندگان
چکیده
منابع مشابه
Dynamic Local Search for the Maximum Clique Problem
In this paper, we introduce DLS-MC, a new stochastic local search algorithm for the maximum clique problem. DLS-MC alternates between phases of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, during which vertices of the current clique are swapped with vertices not contained in the current clique. The selection of vertices is solely bas...
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In this paper, we propose an effective local search algorithm based on variable depth search (VDS) for the MCP. The VDS has been first successfully applied by Lin and Kernighan to the traveling salesman problem [5] and the graph partitioning problem [4]. Their algorithms are often called k-opt local search. The basic concept of the k-opt local search based on VDS is to search a portion of large...
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This paper introduces Phased Local Search (PLS), a new stochastic reactive dynamic local search algorithm for the maximum clique problem. PLS interleaves sub-algorithms which alternate between sequences of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, where vertices of the current clique are swapped with vertices not contained in the ...
متن کاملCooperating local search for the maximum clique problem
The advent of desktop multi-core computers has dramatically improved the usability of parallel algorithms which, in the past, have required specialised hardware. This paper introduces cooperating local search (CLS), a parallelised hyper-heuristic for the maximum clique problem. CLS utilises cooperating low level heuristics which alternate between sequences of iterative improvement, during which...
متن کاملIterated k-Opt Local Search for the Maximum Clique Problem
This paper presents a simple iterated local search metaheuristic incorporating a k-opt local search (KLS), called Iterated KLS (IKLS for short), for solving the maximum clique problem (MCP). IKLS consists of three components: LocalSearch at which KLS is used, a Kick called LEC-Kick that escapes from local optima, and Restart that occasionally diversifies the search by moving to other points in ...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2006
ISSN: 1076-9757
DOI: 10.1613/jair.1815