LEADER 06288nam 2200829 450 001 9910139135903321 005 20220112144643.0 010 $a1-118-76274-6 010 $a1-118-76275-4 010 $a1-118-76276-2 035 $a(CKB)2550000001272987 035 $a(EBL)1666485 035 $a(SSID)ssj0001181329 035 $a(PQKBManifestationID)11794367 035 $a(PQKBTitleCode)TC0001181329 035 $a(PQKBWorkID)11143195 035 $a(PQKB)10926848 035 $a(DLC) 2014004914 035 $a(Au-PeEL)EBL1666485 035 $a(CaPaEBR)ebr10860998 035 $a(CaONFJC)MIL595114 035 $a(OCoLC)869920891 035 $a(CaSebORM)9781118762752 035 $a(MiAaPQ)EBC1666485 035 $a(PPN)189355352 035 $a(EXLCZ)992550000001272987 100 $a20140502h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDiscrete-event simulation and system dynamics for management decision making /$feditors, Sally Brailsford, Leonid Churilov, Brian Dangerfield ; Steffen Bayer [and twenty one others], contributors 205 $a1st edition 210 1$aChichester, England :$cWiley,$d2014. 210 4$d©2014 215 $a1 online resource (362 p.) 225 1 $aWiley Series in Operations Research and Management Science 300 $aDescription based upon print version of record. 311 $a1-118-34902-4 311 $a1-306-63863-1 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aDiscrete-Event Simulation and System Dynamics for Management Decision Making; Contents; Preface; List of contributors; 1 Introduction; 1.1 How this book came about; 1.2 The editors; 1.3 Navigating the book; References; 2 Discrete-event simulation: A primer; 2.1 Introduction; 2.2 An example of a discrete-event simulation: Modelling a hospital theatres process; 2.3 The technical perspective: How DES works; 2.3.1 Time handling in DES; 2.3.2 Random sampling in DES; 2.4 The philosophical perspective: The DES worldview; 2.5 Software for DES; 2.6 Conclusion; References 327 $a3 Systems thinking and system dynamics: A primer3.1 Introduction; 3.2 Systems thinking; 3.2.1 'Behaviour over time' graphs; 3.2.2 Archetypes; 3.2.3 Principles of influence (or causal loop) diagrams; 3.2.4 From diagrams to behaviour; 3.3 System dynamics; 3.3.1 Principles of stock-.ow diagramming; 3.3.2 Model purpose and model conceptualisation; 3.3.3 Adding auxiliaries, parameters and information links to the spinal stock-flow structure; 3.3.4 Equation writing and dimensional checking; 3.4 Some further important issues in SD modelling; 3.4.1 Use of soft variables; 3.4.2 Co-flows 327 $a3.4.3 Delays and smoothing functions3.4.4 Model validation; 3.4.5 Optimisation of SD models; 3.4.6 The role of data in SD models; 3.5 Further reading; References; 4 Combining problem structuring methods with simulation: The philosophical and practical challenges; 4.1 Introduction; 4.2 What are problem structuring methods?; 4.3 Multiparadigm multimethodology in management science; 4.3.1 Paradigm incommensurability; 4.3.2 Cultural difficulties; 4.3.3 Cognitive difficulties; 4.3.4 Practical problems; 4.4 Relevant projects and case studies; 4.5 The case study: Evaluating intermediate care 327 $a4.5.1 The problem situation4.5.2 Soft systems methodology; 4.5.3 Discrete-event simulation modelling; 4.5.4 Multimethodology; 4.6 Discussion; 4.6.1 The multiparadigm multimethodology position and strategy; 4.6.2 The cultural difficulties; 4.6.3 The cognitive difficulties; 4.7 Conclusions; Acknowledgements; References; 5 Philosophical positioning of discrete-event simulation and system dynamics as management science tools for process systems: A critical realist perspective; 5.1 Introduction; 5.2 Ontological and epistemological assumptions of CR; 5.2.1 The stratified CR ontology 327 $a5.2.2 The abductive mode of reasoning5.3 Process system modelling with SD and DES through the prism of CR scientific positioning; 5.3.1 Lifecycle perspective on SD and DES methods; 5.4 Process system modelling with SD and DES: Trends in and implications for MS; 5.5 Summary and conclusions; References; 6 Theoretical comparison of discrete-event simulation and system dynamics; 6.1 Introduction; 6.2 System dynamics; 6.3 Discrete-event simulation; 6.4 Summary: The basic differences; 6.5 Example: Modelling emergency care in Nottingham; 6.5.1 Background; 6.5.2 The ECOD project 327 $a6.5.3 Choice of modelling approach 330 $a"In recent years, there has been a growing debate, particularly in the UK and Europe, over the merits of using discrete-event simulation (DES) and system dynamics (SD); there are now instances where both methodologies were employed on the same problem. This book details each method, comparing each in terms of both theory and their application to various problem situations. It also provides a seamless treatment of various topics--theory, philosophy, detailed mechanics, practical implementation--providing a systematic treatment of the methodologies of DES and SD, which previously have been treated separately. "--$cProvided by publisher. 330 $a"Explores the integration of discrete-event simulation (DES) and system dynamics (SD), providing comparisons of each methodology"--$cProvided by publisher. 410 0$aWiley series in operations research and management science. 606 $aDiscrete-time systems$xSimulation methods 606 $aSystem analysis 606 $aDecision making 606 $aManagement science 615 0$aDiscrete-time systems$xSimulation methods. 615 0$aSystem analysis. 615 0$aDecision making. 615 0$aManagement science. 676 $a658.4/0352 686 $aTEC029000$2bisacsh 702 $aBrailsford$b Sally 702 $aChurilov$b Leonid 702 $aDangerfield$b Brian Thornley 702 $aBayer$b Steffen 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139135903321 996 $aDiscrete-event simulation and system dynamics for management decision making$92127674 997 $aUNINA LEADER 01157nam a2200241 u 4500 001 991004310838407536 005 20240306103053.0 008 240306s1995 it r 001 0 ita d 040 $aBibl. Dip.le Aggr. Scienze Economia - Sez. 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