A probabilistic greedy search algorithm for combinatorial optimisation with application to the set covering problem

We present a probabilistic greedy search method for combinatorial optimisation problems. This approach is implemented and evaluated for the Set Covering Problem (SCP) and shown to yield a simple, robust, and quite fast heuristic. Tests performed on a large set of benchmark instances with up to 1000...

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Veröffentlicht in:	The Journal of the Operational Research Society 2002-07, Vol.53 (7), p.792-799
Hauptverfasser:	Haouari, M, Chaouachi, J S
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Business and Management combinatorial optimisation Combinatorial optimization Exact sciences and technology Experimentation Flows in networks. Combinatorial problems Genetic algorithms Greedy algorithms greedy method Heuristic Heuristics Lagrangian function Management Minimization of cost Operational research and scientific management Operational research. Management science Operations research Operations Research/Decision Theory Optimization Probability Scheduling set covering problem Studies Theoretical Paper Theoretical Papers
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Beschreibung
Zusammenfassung:	We present a probabilistic greedy search method for combinatorial optimisation problems. This approach is implemented and evaluated for the Set Covering Problem (SCP) and shown to yield a simple, robust, and quite fast heuristic. Tests performed on a large set of benchmark instances with up to 1000 rows and 10 000 columns show that the algorithm consistently yields near-optimal solutions.
ISSN:	0160-5682 1476-9360
DOI:	10.1057/palgrave.jors.2601366