000 | 03897nam a22005055i 4500 | ||
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001 | 978-3-540-78985-7 | ||
003 | DE-He213 | ||
005 | 20170628034851.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2008 gw | s |||| 0|eng d | ||
020 |
_a9783540789857 _9978-3-540-78985-7 |
||
024 | 7 |
_a10.1007/978-3-540-78985-7 _2doi |
|
050 | 4 | _aTA329-348 | |
050 | 4 | _aTA640-643 | |
072 | 7 |
_aTBJ _2bicssc |
|
072 | 7 |
_aMAT003000 _2bisacsh |
|
082 | 0 | 4 |
_a519 _223 |
100 | 1 |
_aXhafa, Fatos. _eeditor. |
|
245 | 1 | 0 |
_aMetaheuristics for Scheduling in Industrial and Manufacturing Applications _h[electronic resource] / _cedited by Fatos Xhafa, Ajith Abraham. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2008. |
|
300 |
_aXXIV, 346 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aStudies in Computational Intelligence, _x1860-949X ; _v128 |
|
505 | 0 | _aExact, Heuristic and Meta-heuristic Algorithms for Solving Shop Scheduling Problems -- Scatter Search Algorithms for Identical Parallel Machine Scheduling Problems -- On the Effectiveness of Particle Swarm Optimization and Variable Neighborhood Descent for the Continuous Flow-Shop Scheduling Problem -- A Dynamical Ant Colony Optimization with Heuristics for Scheduling Jobs on a Single Machine with a Common Due Date -- Deterministic Search Algorithm for Sequencing and Scheduling -- Sequential and Parallel Variable Neighborhood Search Algorithms for Job Shop Scheduling -- Solving Scheduling Problems by Evolutionary Algorithms for Graph Coloring Problem -- Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: a comparison study -- Hybrid Heuristic Approaches for Scheduling in Reconfigurable Manufacturing Systems -- A Genetic Algorithm for Railway Scheduling Problems -- Modelling Process and Supply Chain Scheduling Using Hybrid Meta-heuristics -- Combining Simulation and Tabu Search for Oil-derivatives Pipeline Scheduling -- Particle Swarm Scheduling for Work-Flow Applications in Distributed Computing Environments. | |
520 | _aDuring the past decades scheduling has been among the most studied optimization problems and it is still an active area of research! Scheduling appears in many areas of science, engineering and industry and takes different forms depending on the restrictions and optimization criteria of the operating environments. This book deals with the application of various novel metaheuristics in scheduling. Addressing the various issues of scheduling in industrial and manufacturing applications is the novelty of this edited volume. Important features include the detailed overview of the various novel metaheuristic scheduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and scheduling will find the comprehensive coverage of this book invaluable. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aInformation systems. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aEngineering mathematics. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aAppl.Mathematics/Computational Methods of Engineering. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aInformation Systems Applications (incl.Internet). |
700 | 1 |
_aAbraham, Ajith. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540789840 |
830 | 0 |
_aStudies in Computational Intelligence, _x1860-949X ; _v128 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-540-78985-7 |
912 | _aZDB-2-ENG | ||
999 |
_c21874 _d21874 |