R. K. Ahuja, O. Ergun, J. B. Orlin, and A. P. Punnen. A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123(1-3):75--102, 2002. Home/Search Document Not in Database Summary Related Articles Check |
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A Very Large-Scale Neighborhood Search Algorithm for the .. - Yagiura, Iwasaki.. (2004) (1 citation) (Correct)
.... have been proposed for GAP [3, 4, 7, 10, 11] Our algorithm is based on tabu search, and features a very large scale neighborhood search, which is a mechanism of conducting the search with complex and powerful moves, where the resulting neighborhood is e#ciently searched via the improvement graph [1, 2]. We also incorporate an automatic mechanism for adjusting search parameters, to maintain a balance between visits to feasible and infeasible regions. We conducted computational experiment on benchmark instances called types C, D and E, and compared the proposed method with other existing ....
....words, for r = 2, 3, l, job j r is shifted from agent #(j r ) to agent #(j r 1 ) after ejecting job j r 1 . This is based on the idea of ejection chains by Glover [6] Since the size of such a neighborhood can become exponential, we carefully limit its size by utilizing improvement graphs [1, 2]. Since N shift swap chain holds, N swap is searched only if N shift does not contain an improving solution, and N chain is searched only if N shift N swap does not contain an improving solution unless otherwise stated. When the search visits the infeasible region, we evaluate the ....
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R.K. Ahuja, O. Ergun, J.B. Orlin, and A.P. Punnen, "A survey of very large-scale neighborhood search techniques," Discrete Applied Mathematics, 123 (2002) 75--102.
Effective Local Search Algorithms for the Vehicle.. - Ibaraki, Kubo.. (2002) (1 citation) (Correct)
....the cross exchange, 2 opt and Or opt neighborhoods, have been widely used [19, 21, 22, 26] We refer to these neighborhoods as standard neighborhoods. In our local search, in addition to these standard neighborhoods, we use a new type of neighborhood called the cyclic exchange neighborhood [1, 3]. This is de ned to be the set of solutions obtainable by cyclically exchanging two or more paths of length at most L cyclic (a parameter) As the size of this neighborhood grows exponentially with the input size, an improving solution is searched by using the improvement graph, whose concept is ....
.... be the set of solutions obtainable by cyclically exchanging two or more paths of length at most L cyclic (a parameter) As the size of this neighborhood grows exponentially with the input size, an improving solution is searched by using the improvement graph, whose concept is proposed, e.g. in [1, 3], and is applicable to wide range of problems. We also propose time oriented neighbor lists to make the search in the cross exchange and 2 opt neighborhoods more ecient. Among many possible metaheuristics based on local search, we use the multi start local search (MLS) the iterated local ....
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R.K. Ahuja, O. Ergun, J.B. Orlin, A.P. Punnen, \A survey of very large-scale neighborhood search techniques," Discrete Applied Mathematics, to appear.
A Multi-Exchange Neighborhood for Minimum Makespan .. - Frangioni.. (2000) (3 citations) (Correct)
....As known from the literature, several algorithms can be derived from this general framework by suitably implementing the set Q. When enriched with a cycle detection strategy, these algorithms can be used to identify, in polynomial time, unrestricted) negative cycles in the input graph G (Cherkassky and Goldberg, 1999). Starting from the general label correcting framework, we propose two heuristic approaches, K SPT and 1 SPT , which use the cost de nition (1) for nding K disjoint cycles (paths) and 1 disjoint cycles (paths) respectively, in G(S) In addition to the labels d(j) and pred(j) associated with each ....
R.K. Ahuja, O. Ergun, J.B. Orlin and A.P. Punnen, \A survey of very large-scale neighborhood search techniques", Working Paper, Center for Applied Optimization, University of Florida, 1999.
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R. Ahuja, O. Ergun, J. Orlin, and A. Punnen. A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123:75--102, 2002.
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R. K. Ahuja, O. Ergun, J. B. Orlin, and A. P. Punnen. A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123(1-3):75--102, 2002.
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R. Ahuja, O. Ergun, J. Orlin, and A. Punnen. A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123:75--102, 2002.
A Multi-start Very Large Neighbourhood Search Approach with.. - Abdullah, Burke (2006) (Correct)
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Ahuja, R.K., Ozlem Ergun, Orlin, J.B., Abraham, O. Punnen. 2001. A Survey Of Very Large-scale Neighborhood Search Techniques. Discrete Applied Mathematics 123, 75102.
Unknown - Paris September Multi-Exchange (Correct)
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R.K. Ahuja, O. Ergun, J.B. Orlin, and A.P. Punnen. A survey of very large-scale neighborhood search techniques. Working paper, July 1999.
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R.K. Ahuja, O. Ergun, J.B. Orlin, and A.P. Punnen, "A survey of very large-scale neighborhood search techniques," Discrete Applied Mathematics, 123 (2002) 75--102.
Hybrid Method to Optimize Petroleum Extraction in Deep.. - Nascimento, Moura, de.. (2002) (Correct)
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R. K. Ahuja, O. Ergun, J. B. Orlin, and A. P. Punnen. A survey of very large-scale neighborhood search techniques. Taken from the net web site: web.mit.edu/jorlin/www, directory working papers, July 1999.
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