LEADER 04270nam 22006615 450 001 9910734094903321 005 20251202135646.0 010 $a1-4614-6322-X 024 7 $a10.1007/978-1-4614-6322-1 035 $a(CKB)2670000000340902 035 $a(EBL)1106261 035 $a(OCoLC)829936666 035 $a(SSID)ssj0000870667 035 $a(PQKBManifestationID)11454955 035 $a(PQKBTitleCode)TC0000870667 035 $a(PQKBWorkID)10818557 035 $a(PQKB)11613847 035 $a(DE-He213)978-1-4614-6322-1 035 $a(MiAaPQ)EBC1106261 035 $a(PPN)168305054 035 $a(EXLCZ)992670000000340902 100 $a20130228d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Metaheuristics /$fedited by Luca Di Gaspero, Andrea Schaerf, Thomas Stützle 205 $a1st ed. 2013. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2013. 215 $a1 online resource (192 p.) 225 1 $aOperations Research/Computer Science Interfaces Series,$x2698-5489 ;$v53 300 $aDescription based upon print version of record. 311 08$a1-4899-9187-5 311 08$a1-4614-6321-1 320 $aIncludes bibliographical references. 327 $aFinite First Hitting Time versus Stochastic convergence in Particle Swarm Optimisation -- Using Performance Profiles for the Analysis and Design of Benchmark Experiments -- Real-World Parameter Tuning using Factorial Design with Parameter Decomposition -- Evolving Pacing Strategies for Team Pursuit Track Cycling -- A Dual Mutation Operator to Solve the Multi-objective Production Planning of Perishable Goods -- Brain cine-MRI Registration using MLSDO Dynamic Optimization Algorithm -- GRASP with Path Relinking for the Two-Echelon Vehicle Routing Problem -- A Hybrid (1+1)-Evolutionary Strategy for the Open Vehicle Routing Problem -- A Timeslot-Filling Heuristic Approach to Construct High-School Timetables -- A GRASP for Supply Chain Optimization with Financial Constraints per Production Unit. 330 $aMetaheuristics have been a very active research topic for more than two decades. During this time many new metaheuristic strategies have been devised, they have been experimentally tested and improved on challenging benchmark problems, and they have proven to be important tools for tackling optimization tasks in a large number of practical applications. In other words, metaheuristics are nowadays established as one of the main search paradigms for tackling computationally hard problems. Still, there are a large number of research challenges in the area of metaheuristics. These challenges range from more fundamental questions on theoretical properties and performance guarantees, empirical algorithm analysis, the effective configuration of metaheuristic algorithms, approaches to combine metaheuristics with other algorithmic techniques, towards extending the available techniques to tackle ever more challenging problems. This edited volume grew out of the contributions presented at the ninth Metaheuristics International Conference that was held in Udine, Italy, 25-28 July 2011. The conference comprised 117 presentations of peer-reviewed contributions and 3 invited talks, and it has been attended by 169 delegates. The chapters that are collected in this book exemplify contributions to several of the research directions outlined above. 410 0$aOperations Research/Computer Science Interfaces Series,$x2698-5489 ;$v53 606 $aOperations research 606 $aManagement science 606 $aOperations Research and Decision Theory 606 $aOperations Research, Management Science 615 0$aOperations research. 615 0$aManagement science. 615 14$aOperations Research and Decision Theory. 615 24$aOperations Research, Management Science. 676 $a519.6 701 $aDi Gaspero$b Luca$0607115 701 $aSchaerf$b Andrea$01759409 701 $aStutzle$b Thomas$0432894 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910734094903321 996 $aAdvances in metaheuristics$94197857 997 $aUNINA