On the best search strategy in parallel branch and bound best first search vs. lazy depth first search:
Abstract: "The Best-First-Search strategy (BeFS) and the Depth- First-Search strategy (DFS) are regarded as the prime strategies when solving combinatorial optimization problems by parallel Branch-and-Bound (B & B) -- BeFS because of efficiency with respect to number of nodes explored, and...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
København
1996
|
| Schriftenreihe: | Datalogisk Institut <København>: DIKU-Rapport
1996,16 |
| Schlagworte: | |
| Zusammenfassung: | Abstract: "The Best-First-Search strategy (BeFS) and the Depth- First-Search strategy (DFS) are regarded as the prime strategies when solving combinatorial optimization problems by parallel Branch-and-Bound (B & B) -- BeFS because of efficiency with respect to number of nodes explored, and DFS for reasons of space efficiency. We investigate the efficiency of both strategies experimentally, and two versions of each strategy are tested: In the first, B & B-iteration for a node consists of bounding followed by branching on the node if necessary. For the second, the order is reversed -- first branching takes place, and then each child of the node is bounded and possibly fathomed. The first is called lazy, the second eager. The strategies are tested on the Quadratic Assignment Problem and the Job Shop Scheduling Problem. We use parallel codes developed specificly [sic] for the solution of the problem in question, and hence containing different heuristic rules and tests to speed up computation. In both cases we start with an initial solution close to but not equal to the optimal solution. Surprisingly, the BeFS-based strategies turn out to be inferior to the DFS-based strategies, both in terms of running times and in terms of bound calculations performed. Furthermore, when tested in a sequential setting BeFS turns out still to be inferior and again due to the problem-dependent efficiency enhancing parts of the computation." |
| Beschreibung: | 13 S. |
Internformat
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| 100 | 1 | |a Clausen, Jens |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a On the best search strategy in parallel branch and bound best first search vs. lazy depth first search |c Jens Clausen and Michael Perregaard |
| 264 | 1 | |a København |c 1996 | |
| 300 | |a 13 S. | ||
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| 520 | 3 | |a Abstract: "The Best-First-Search strategy (BeFS) and the Depth- First-Search strategy (DFS) are regarded as the prime strategies when solving combinatorial optimization problems by parallel Branch-and-Bound (B & B) -- BeFS because of efficiency with respect to number of nodes explored, and DFS for reasons of space efficiency. We investigate the efficiency of both strategies experimentally, and two versions of each strategy are tested: In the first, B & B-iteration for a node consists of bounding followed by branching on the node if necessary. For the second, the order is reversed -- first branching takes place, and then each child of the node is bounded and possibly fathomed. The first is called lazy, the second eager. The strategies are tested on the Quadratic Assignment Problem and the Job Shop Scheduling Problem. We use parallel codes developed specificly [sic] for the solution of the problem in question, and hence containing different heuristic rules and tests to speed up computation. In both cases we start with an initial solution close to but not equal to the optimal solution. Surprisingly, the BeFS-based strategies turn out to be inferior to the DFS-based strategies, both in terms of running times and in terms of bound calculations performed. Furthermore, when tested in a sequential setting BeFS turns out still to be inferior and again due to the problem-dependent efficiency enhancing parts of the computation." | |
| 650 | 4 | |a Branch and bound algorithms | |
| 650 | 4 | |a Combinatorial optimization | |
| 650 | 4 | |a Operations research | |
| 650 | 4 | |a Parallel processing (Electronic computers) | |
| 700 | 1 | |a Perregaard, Michael |e Verfasser |4 aut | |
| 830 | 0 | |a Datalogisk Institut <København>: DIKU-Rapport |v 1996,16 |w (DE-604)BV010011493 |9 1996,16 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-007416717 | ||
Datensatz im Suchindex
| _version_ | 1804125562589937664 |
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| any_adam_object | |
| author | Clausen, Jens Perregaard, Michael |
| author_facet | Clausen, Jens Perregaard, Michael |
| author_role | aut aut |
| author_sort | Clausen, Jens |
| author_variant | j c jc m p mp |
| building | Verbundindex |
| bvnumber | BV011072355 |
| ctrlnum | (OCoLC)38963481 (DE-599)BVBBV011072355 |
| format | Book |
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| id | DE-604.BV011072355 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T18:03:32Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007416717 |
| oclc_num | 38963481 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | 13 S. |
| publishDate | 1996 |
| publishDateSearch | 1996 |
| publishDateSort | 1996 |
| record_format | marc |
| series | Datalogisk Institut <København>: DIKU-Rapport |
| series2 | Datalogisk Institut <København>: DIKU-Rapport |
| spelling | Clausen, Jens Verfasser aut On the best search strategy in parallel branch and bound best first search vs. lazy depth first search Jens Clausen and Michael Perregaard København 1996 13 S. txt rdacontent n rdamedia nc rdacarrier Datalogisk Institut <København>: DIKU-Rapport 1996,16 Abstract: "The Best-First-Search strategy (BeFS) and the Depth- First-Search strategy (DFS) are regarded as the prime strategies when solving combinatorial optimization problems by parallel Branch-and-Bound (B & B) -- BeFS because of efficiency with respect to number of nodes explored, and DFS for reasons of space efficiency. We investigate the efficiency of both strategies experimentally, and two versions of each strategy are tested: In the first, B & B-iteration for a node consists of bounding followed by branching on the node if necessary. For the second, the order is reversed -- first branching takes place, and then each child of the node is bounded and possibly fathomed. The first is called lazy, the second eager. The strategies are tested on the Quadratic Assignment Problem and the Job Shop Scheduling Problem. We use parallel codes developed specificly [sic] for the solution of the problem in question, and hence containing different heuristic rules and tests to speed up computation. In both cases we start with an initial solution close to but not equal to the optimal solution. Surprisingly, the BeFS-based strategies turn out to be inferior to the DFS-based strategies, both in terms of running times and in terms of bound calculations performed. Furthermore, when tested in a sequential setting BeFS turns out still to be inferior and again due to the problem-dependent efficiency enhancing parts of the computation." Branch and bound algorithms Combinatorial optimization Operations research Parallel processing (Electronic computers) Perregaard, Michael Verfasser aut Datalogisk Institut <København>: DIKU-Rapport 1996,16 (DE-604)BV010011493 1996,16 |
| spellingShingle | Clausen, Jens Perregaard, Michael On the best search strategy in parallel branch and bound best first search vs. lazy depth first search Datalogisk Institut <København>: DIKU-Rapport Branch and bound algorithms Combinatorial optimization Operations research Parallel processing (Electronic computers) |
| title | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search |
| title_auth | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search |
| title_exact_search | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search |
| title_full | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search Jens Clausen and Michael Perregaard |
| title_fullStr | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search Jens Clausen and Michael Perregaard |
| title_full_unstemmed | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search Jens Clausen and Michael Perregaard |
| title_short | On the best search strategy in parallel branch and bound best first search vs. lazy depth first search |
| title_sort | on the best search strategy in parallel branch and bound best first search vs lazy depth first search |
| topic | Branch and bound algorithms Combinatorial optimization Operations research Parallel processing (Electronic computers) |
| topic_facet | Branch and bound algorithms Combinatorial optimization Operations research Parallel processing (Electronic computers) |
| volume_link | (DE-604)BV010011493 |
| work_keys_str_mv | AT clausenjens onthebestsearchstrategyinparallelbranchandboundbestfirstsearchvslazydepthfirstsearch AT perregaardmichael onthebestsearchstrategyinparallelbranchandboundbestfirstsearchvslazydepthfirstsearch |