LEADER 05647nam 22007815 450 001 996466112503316 005 20230405233803.0 010 $a3-540-46385-2 024 7 $a10.1007/11890584 035 $a(CKB)1000000000283874 035 $a(SSID)ssj0000318177 035 $a(PQKBManifestationID)11233958 035 $a(PQKBTitleCode)TC0000318177 035 $a(PQKBWorkID)10307954 035 $a(PQKB)11367019 035 $a(DE-He213)978-3-540-46385-6 035 $a(MiAaPQ)EBC3068505 035 $a(PPN)123139015 035 $a(EXLCZ)991000000000283874 100 $a20100301d2006 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aHybrid Metaheuristics$b[electronic resource] $eThird International Workshop, HM 2006, Gran Canaria, Spain, October 13-14, 2006, Proceedings /$fedited by Francisco Almeida, María J. Blesa Aguilera, Christian Blum, José Marcos Moreno Vega, Melquíades Pérez, Andrea Roli, MIchael Sampels 205 $a1st ed. 2006. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2006. 215 $a1 online resource (X, 193 p.) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v4030 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-46384-4 320 $aIncludes bibliographical references and index. 327 $aA Unified View on Hybrid Metaheuristics -- Packing Problems with Soft Rectangles -- A Multi-population Parallel Genetic Algorithm for Highly Constrained Continuous Galvanizing Line Scheduling -- Improvement in the Performance of Island Based Genetic Algorithms Through Path Relinking -- Using Datamining Techniques to Help Metaheuristics: A Short Survey -- An Iterated Local Search Heuristic for a Capacitated Hub Location Problem -- Using Memory to Improve the VNS Metaheuristic for the Design of SDH/WDM Networks -- Multi-level Ant Colony Optimization for DNA Sequencing by Hybridization -- Hybrid Approaches for Rostering: A Case Study in the Integration of Constraint Programming and Local Search -- A Reactive Greedy Randomized Variable Neighborhood Tabu Search for the Vehicle Routing Problem with Time Windows -- Incorporating Inference into Evolutionary Algorithms for Max-CSP -- Scheduling Social Golfers with Memetic Evolutionary Programming -- Colour Reassignment in Tabu Search for the Graph Set T-Colouring Problem -- Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations. 330 $aThe International Workshop on Hybrid Metaheuristics reached its third edition with HM 2006. The active and successful participation in the past editions was a clear indication that the research community on metaheuristics and related areas felt the need for a forum to discuss speci?c aspects of hybridization of metaheuristics. The selection of papers for HM 2006 consolidated some of the mainstream issues that have emerged from the past editions. Firstly, there are prominent examples of e?ective hybrid techniques whose design and implementation were motivated by challenging real-world applications. We believe this is particularly important for two reasons: on the one hand, researchers are conscious that the primary goal of developing algorithms is to solve relevant real-life problems; on the other hand, the path towarde?cient solving methods for practical problems is a source of new outstanding ideas and theories. A second important issue is that the research community on metaheur- tics has become increasingly interested in and open to techniques and methods known from arti?cial intelligence (AI) and operations research (OR). So far, the most representative examples of such integration have been the use of AI/OR techniques as subordinates of metaheuristic methods. As a historical and - ymological note, this is in perfect accordance with the original meaning of a metaheuristic as a ?general strategy controlling a subordinate heuristic. ? The awareness of the need for a sound experimental methodology is a third keypoint. 410 0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v4030 606 $aArtificial intelligence 606 $aAlgorithms 606 $aComputer science 606 $aNumerical analysis 606 $aPattern recognition systems 606 $aArtificial Intelligence 606 $aAlgorithms 606 $aTheory of Computation 606 $aNumerical Analysis 606 $aAutomated Pattern Recognition 615 0$aArtificial intelligence. 615 0$aAlgorithms. 615 0$aComputer science. 615 0$aNumerical analysis. 615 0$aPattern recognition systems. 615 14$aArtificial Intelligence. 615 24$aAlgorithms. 615 24$aTheory of Computation. 615 24$aNumerical Analysis. 615 24$aAutomated Pattern Recognition. 676 $a006.3 702 $aAlmeida$b Francisco$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBlesa Aguilera$b María J$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBlum$b Christian$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMoreno Vega$b José Marcos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPérez$b Melquíades$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRoli$b Andrea$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSampels$b MIchael$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996466112503316 996 $aHybrid Metaheuristics$9772372 997 $aUNISA