Title | ||
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A metaheuristic framework for stochastic combinatorial optimization problems based on GPGPU with a case study on the probabilistic traveling salesman problem with deadlines |
Abstract | ||
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In this work we propose a general metaheuristic framework for solving stochastic combinatorial optimization problems based on general-purpose computing on graphics processing units (GPGPU). This framework is applied to the probabilistic traveling salesman problem with deadlines (PTSPD) as a case study. Computational studies reveal significant improvements over state-of-the-art methods for the PTSPD. Additionally, our results reveal the huge potential of the proposed framework and sampling-based methods for stochastic combinatorial optimization problems. |
Year | DOI | Venue |
---|---|---|
2013 | 10.1016/j.jpdc.2012.05.004 | J. Parallel Distrib. Comput. |
Keywords | Field | DocType |
general metaheuristic framework,sampling-based method,proposed framework,stochastic combinatorial optimization problem,salesman problem,huge potential,significant improvement,general-purpose computing,case study,computational study,monte carlo sampling,gpgpu | Graphics,Stochastic optimization,Mathematical optimization,Computer science,CUDA,Combinatorial optimization,Cross-entropy method,Theoretical computer science,General-purpose computing on graphics processing units,Optimization problem,Metaheuristic | Journal |
Volume | Issue | ISSN |
73 | 1 | 0743-7315 |
Citations | PageRank | References |
3 | 0.39 | 23 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dennis Weyland | 1 | 108 | 8.43 |
Roberto Montemanni | 2 | 643 | 44.25 |
Luca Maria Gambardella | 3 | 7926 | 726.40 |