Generation of feasible integer solutions on a massively parallel computer using the feasibility pump
We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP i...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Koc, Utku [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Umfang: |
7 |
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| Übergeordnetes Werk: |
Enthalten in: Impact of Lung Flute Therapy on Asthma: A Pilot Study - Parikh, Neil U. ELSEVIER, 2017, a journal of INFORMS devoted to the rapid publication of concise contributions in operations research, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:45 ; year:2017 ; number:6 ; pages:652-658 ; extent:7 |
| Links: |
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| DOI / URN: |
10.1016/j.orl.2017.10.003 |
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ELV041075463 |
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| 520 | |a We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. | ||
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10.1016/j.orl.2017.10.003 doi GBV00000000000038.pica (DE-627)ELV041075463 (ELSEVIER)S0167-6377(17)30560-6 DE-627 ger DE-627 rakwb eng 650 650 DE-600 610 VZ 610 VZ 44.85 bkl Koc, Utku verfasserin aut Generation of feasible integer solutions on a massively parallel computer using the feasibility pump 2017 7 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. Parallel optimization Elsevier Feasibility pump Elsevier Mixed integer programming Elsevier Mehrotra, Sanjay oth Enthalten in Elsevier Science Parikh, Neil U. ELSEVIER Impact of Lung Flute Therapy on Asthma: A Pilot Study 2017 a journal of INFORMS devoted to the rapid publication of concise contributions in operations research Amsterdam [u.a.] (DE-627)ELV014727307 volume:45 year:2017 number:6 pages:652-658 extent:7 https://doi.org/10.1016/j.orl.2017.10.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.85 Kardiologie Angiologie VZ AR 45 2017 6 652-658 7 045F 650 |
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We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. |
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We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. |
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We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. |
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