A parallel approach to bi-objective integer programming
Sábháilte in:
| Foilsithe in: | arXiv.org (Jan 31, 2017), p. n/a |
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| Príomhchruthaitheoir: | |
| Rannpháirtithe: | |
| Foilsithe / Cruthaithe: |
Cornell University Library, arXiv.org
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| Ábhair: | |
| Rochtain ar líne: | Citation/Abstract Full text outside of ProQuest |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 2074115248 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 024 | 7 | |a 10.21914/anziamj.v58i0.11724 |2 doi | |
| 035 | |a 2074115248 | ||
| 045 | 0 | |b d20170131 | |
| 100 | 1 | |a Pettersson, William | |
| 245 | 1 | |a A parallel approach to bi-objective integer programming | |
| 260 | |b Cornell University Library, arXiv.org |c Jan 31, 2017 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a To obtain a better understanding of the trade-offs between various objectives, Bi-Objective Integer Programming (BOIP) algorithms calculate the set of all non-dominated vectors and present these as the solution to a BOIP problem. Historically, these algorithms have been compared in terms of the number of single-objective IPs solved and total CPU time taken to produce the solution to a problem. This is equitable, as researchers can often have access to widely differing amounts of computing power. However, the real world has recently seen a large uptake of multi-core processors in computers, laptops, tablets and even mobile phones. With this in mind, we look at how to best utilise parallel processing to improve the elapsed time of optimisation algorithms. We present two methods of parallelising the recursive algorithm presented by Ozlen, Burton and MacRae. Both new methods utilise two threads and improve running times. One of the new methods, the Meeting algorithm, halves running time to achieve near-perfect parallelisation. The results are compared with the efficiency of parallelisation within the commercial IP solver IBM ILOG CPLEX, and the new methods are both shown to perform better. | |
| 653 | |a Parallel processing | ||
| 653 | |a Algorithms | ||
| 653 | |a Integer programming | ||
| 653 | |a Microprocessors | ||
| 653 | |a Tablets | ||
| 653 | |a Optimization | ||
| 653 | |a Recursive methods | ||
| 653 | |a Run time (computers) | ||
| 700 | 1 | |a Ozlen, Melih | |
| 773 | 0 | |t arXiv.org |g (Jan 31, 2017), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2074115248/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/1701.08920 |