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978-3-319-15033-8 |
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20220117150004.0 |
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150406s2015 sz | s |||| 0|eng d |
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|a 9783319150338
|9 978-3-319-15033-8
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|a 10.1007/978-3-319-15033-8
|2 doi
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|a 003.3
|2 23
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|a Applied Simulation and Optimization
|h [electronic resource] :
|b In Logistics, Industrial and Aeronautical Practice /
|c edited by Miguel Mujica Mota, Idalia Flores De La Mota, Daniel Guimarans Serrano.
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250 |
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|a 1st ed. 2015.
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264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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300 |
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|a XV, 319 p. 138 illus., 80 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
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|a Simulation-based Optimization with HeuristicLab: Practical Guidelines and Real World Applications -- Simulation Optimization Approach to solve a complex multiobjective redundancy allocation problem -- OR AND SIMULATION IN COMBINATION FOR OPTIMIZATION -- Tree Search and Simulation -- Integrated solutions for delivery planning and scheduling in distribution centres -- Large Neighbourhood Search and Simulation for Disruption Management in the Airline Industry -- Allocation of Airport check-in counters using a Simulation-Optimization Approach -- Simulation and Optimization of the Pre-hospital Care System of the National University of Mexico -- Simulation Based Optimization Using Greedy Techniques and Simulated Annealing for Optimal Equipment Selection within Print Production Environments -- Linear Bus Holding Model for Real Time Traffic Network Control.
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520 |
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|a Presenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulation's flexibility with optimization techniques' robustness. Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.
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|a Mathematics-Data processing.
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650 |
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|a Engineering mathematics.
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650 |
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|a Engineering-Data processing.
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650 |
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|a Computer simulation.
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650 |
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|a Industrial engineering.
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650 |
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|a Production engineering.
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650 |
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|a Computational Science and Engineering.
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650 |
2 |
4 |
|a Mathematical and Computational Engineering Applications.
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650 |
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|a Computer Modelling.
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650 |
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|a Industrial and Production Engineering.
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700 |
1 |
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|a Mujica Mota, Miguel.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a De La Mota, Idalia Flores.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Guimarans Serrano, Daniel.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
0 |
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|t Springer Nature eBook
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776 |
0 |
8 |
|i Printed edition:
|z 9783319150345
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776 |
0 |
8 |
|i Printed edition:
|z 9783319150321
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776 |
0 |
8 |
|i Printed edition:
|z 9783319357072
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856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/978-3-319-15033-8
|z Texto Completo
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912 |
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|a ZDB-2-SMA
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912 |
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|a ZDB-2-SXMS
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950 |
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|a Mathematics and Statistics (SpringerNature-11649)
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950 |
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
|