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Applied simulation and optimization....

Mujica Mota, Miguel.

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Applied simulation and optimization.. 2,. new applications in logistics, industrial and aeronautical practice

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied simulation and optimization./ edited by Miguel Mujica Mota, Idalia Flores De La Mota.
other author:	Mujica Mota, Miguel.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xiv, 282 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- Introduction -- Supply Chain Problems -- Logistics Problems -- Manufacturing Problems -- Aeronautical Problems -- Big Data Applications -- Conclusions -- Bibliography -- References.
Contained By:	Springer eBooks
Subject:	Simulation methods. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-55810-3
ISBN:	9783319558103

Applied simulation and optimization.. 2,. new applications in logistics, industrial and aeronautical practice
Applied simulation and optimization.2,new applications in logistics, industrial and aeronautical practice[electronic resource] /edited by Miguel Mujica Mota, Idalia Flores De La Mota. - Cham :Springer International Publishing :2017. - xiv, 282 p. :ill., digital ;24 cm.

Preface -- Introduction -- Supply Chain Problems -- Logistics Problems -- Manufacturing Problems -- Aeronautical Problems -- Big Data Applications -- Conclusions -- Bibliography -- References.

Building on the author's earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into the optimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.

ISBN: 9783319558103

Standard No.: 10.1007/978-3-319-55810-3doiSubjects--Topical Terms:

581321
Simulation methods.

LC Class. No.: T57.62

Dewey Class. No.: 003.3

Applied simulation and optimization.. 2,. new applications in logistics, industrial and aeronautical practice
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245 0 0 $a Applied simulation and optimization. $n 2, $p new applications in logistics, industrial and aeronautical practice $h [electronic resource] / $c edited by Miguel Mujica Mota, Idalia Flores De La Mota.
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300 $a xiv, 282 p. : $b ill., digital ; $c 24 cm.
505 0 $a Preface -- Introduction -- Supply Chain Problems -- Logistics Problems -- Manufacturing Problems -- Aeronautical Problems -- Big Data Applications -- Conclusions -- Bibliography -- References.
520 $a Building on the author's earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into the optimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.
650 0 $a Simulation methods. $3 581321
650 0 $a Mathematical optimization. $3 517763
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650 2 4 $a Computational Science and Engineering. $3 893018
650 2 4 $a Appl.Mathematics/Computational Methods of Engineering. $3 890892
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Industrial and Production Engineering. $3 891024
700 1 $a Mujica Mota, Miguel. $3 3242442
700 1 $a Mota, Idalia Flores de la. $3 2145794
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