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020 _a9781461463221
_9978-1-4614-6322-1
024 7 _a10.1007/978-1-4614-6322-1
_2doi
050 4 _aHD30.23
072 7 _aKJT
_2bicssc
072 7 _aKJMD
_2bicssc
072 7 _aBUS049000
_2bisacsh
082 0 4 _a658.40301
_223
245 1 0 _aAdvances in Metaheuristics
_h[electronic resource] /
_cedited by Luca Di Gaspero, Andrea Schaerf, Thomas Stützle.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXIV, 183 p. 52 illus., 18 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aOperations Research/Computer Science Interfaces Series,
_x1387-666X ;
_v53
505 0 _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.
520 _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.
650 0 _aBusiness.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aManagement science.
650 1 4 _aBusiness and Management.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aOperations Research, Management Science.
700 1 _aDi Gaspero, Luca.
_eeditor.
700 1 _aSchaerf, Andrea.
_eeditor.
700 1 _aStützle, Thomas.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461463214
830 0 _aOperations Research/Computer Science Interfaces Series,
_x1387-666X ;
_v53
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-6322-1
912 _aZDB-2-SBE
942 _2Dewey Decimal Classification
_ceBooks
999 _c44604
_d44604