Dynamics in logistics : First International Conference, Ldic 2007, Bremen, Germany, August 2007 Proceedings

Title:

Publication Information:

Berlin : Springer, 2008

Physical Description:

xxi, 465 p. : ill. ; 24 cm.

ISBN:

9783540768616

Subject Term:

Business logistics -- Congresses

Radio frequency identification systems -- Congresses

Knowledge management -- Congresses

Added Author:

Haasis, Hans-Dietrich

Kreowski, Hans-Joerg

Scholz-Reiter, Bernd

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
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Searching... PSZ JB	30000010195386	HD38.5 L39 2008	Open Access Book	Book	Searching... Unknown

Logistic problems can rarely be solved satisfyingly within one single scientific discipline. This cross-sectional character is taken into account by the Research Cluster for Dynamics in Logistics with a combination of economical, information and production technical and enterprise-oriented research approaches. In doing so, the interdisciplinary cooperation between university, research institutes and enterprises for the solution of logistic problems is encouraged.

This book comprises the edited proceedings of the first International Conference on Dynamics in Logistics LDIC 2007. The scope of the conference was concerned with the identification, analysis, and description of the dynamics of logistic processes and networks. The spectrum reached from the planning and modelling of processes over innovative methods like autonomous control and knowledge management to the new technologies provided by radio frequency identification, mobile communication, and networking.

Two invited papers and of 42 contributed papers on various subjects give an state-of-art overview on dynamics in logistics. They include routing in dynamic logistic networks, RFID in logistics and manufacturing networks, supply chain control policies, sustainable collaboration, knowledge management and service models in logistics, container logistics, autonomous control in logistics, and logistic process modelling.

Author Notes

Hans-Dietrich Haasis is full professor for Business Administration, Production Management and Industrial Economics at the University of Bremen and chairman of Business Administration, Production-Management and Industrial Economics, University of Bremen, and director of the ISL - Institute of Shipping Economics and Logistics, Bremen. He held lectures at the Ecole Nationale Supérieure de Pétrole et des Moteurs, Paris Rueil-Malmaison, at the University Eichstätt-Ingolstadt, and at the Private University Witten-Herdecke. He also was invited to give lectures at the St. Petersburg State University of Economics and Finance, and the Technical University of Changcha, China.

Hans-Jörg Kreowski is professor for Theoretical Computer Science at the University of Bremen. His main research topics are graph transformation, formal modelling and their applications in computer science and logistics. He (co)-authored and (co)-edited 15 books and published more than 120 scientific papers.

Bernd Scholz-Reiter was founder and head of the Fraunhofer Application Center for Logistics Systems Planning and Information Systems at Cottbus. Since November 2000 he is a full professor and chair holder of the chair of Planning and Control of Production Systems (PSPS) at the University of Bremen where he also serves as director of the Bremen Institute of Industrial Technology and Applied Work Science (BIBA). He was initiator and vice-speaker of the research group on Autonomous Control of Logistic Processes, speaker of the Bremen Research Cluster for Dynamics in Logistics as well as speaker of the International Graduate School for Dynamics in Logistics. Scholz-Reiter is an ordinary member of the Berlin-Brandenburg Academy of Sciences and Humanities, an ordinary member of acatech, the Council for Engineering Sciences at the Union of the German Academies of Sciences and Humanities; BESIDE OTHER NATIONAL MEMBERSHIIPS he is a member of CIRP, the International Institution for Production Engineering Research, a fellow of the European Academy of Industrial Management (AIM) and an Advisory Board member of the Schlesinger Laboratory at TECHNION - Israel Institute of Technology, Haifa, Israel, as well as a member of the Scientific Advisory Board of the German Logistics Association (BVL). Professor Scholz-Reiter serves as vice president of the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG). He is editor of the professional journals Industrie-Management and PPS-Management and member of the editorial board of the scientific International Journal Production Planning & Control. He is author and co-author of more than 250 scientific publications..

Neil A. DuffleBill Hardgrave and Cynthia K. Riemenschneider and Deborah J. ArmstrongPaul Maropoulos and Maxime Chauve and Catherine Da CunhaRichard Weber and Jose GuajardoTomomi Kito and Kanji UedaHyo Young Bae and Ri Choe and Taejin Park and Kwang Ryel RyuThomas Huth and Dirk C. MattfeldAsvin GoelJohann Riedel and Kulwant S. Pawar and Stefano Torroni and Emilio FerrariAlexander Smirnov and Tatiana Levashova and Nikolay ShilovBéla Pátkai and Damith Ranasinghe and Mark Harrison and Duncan McFarlaneMarco LaumannsMarkus Zschintzsch and Amir Sheikh Jabbari and Walter Lang and Bernd Scholz-ReiterDmitry Ivanov and Marina IvanovaReik Donner and Uwe Hinrichs and Bernd Scholz-ReiterWilhelm Dangelmaier and Benjamin Klöpper and Nando Rüngerer and Mark AufenangerShehla Abbas and Mohamed Mosbah and Akka ZemmariReiner Jedermann and Luis Javier Antúnez Congil and Martin Lorenz and JanD. Gehrke and Walter Lang and Otthein HerzogDieter UckelmannAntonio Rizzi and Roberto Montanari and Andrea Volpi and Massimo TizziAshad Kabir and Bonghee Hong and Wooseok Ryu and Sungwoo AhnReiner Jedermann and Jean-Pierre Emond and Walter LangMichael Hülsmann and Bernd Scholz-Reiter and Christoph de Beer and Linda AusterschulteBernd Scholz-Reiter and Enzo Morosini FrazzonBoris Bemeleit and Martin Lorenz and Jens Schumacher and Otthein HerzogHans-Dietrich HaasisBernd Scholz-Reiter and Salima Delhoum and César StollJukka HemiläSeung Hwan Won and Kap Hwan KimKateryna Daschkovska and Bernd Scholz-ReiterArne Schuldt and Sven WernerTürk Kiziltoprak and René Schumann and Axel Hahn and Jan BehrensKarsten Hölscher and Peter Knirsch and Melanie LudererJörn Schönberger and Herbert KopferGulshanara Singh and Bernd-Ludwig Wenning and Amanpreet Singh and Carmelita GörgSergey Dashkovskiy and Björn Rüffer and Fabian WirthHyerim BaeCarl Hans and Karl A. Hribernik and Klaus-Dieter ThobenRebekka Sputtek and Joerg S. Hofstetter and Wolfgang Stölzle and Phillip KirstRainer MüllerBernd Scholz-Reiter and Thomas Jagalski and Julia C. BendulYoshinao Isobe and Markus RoggenbachMikhail PostanThorsten Schmidt and Guido Follert

Challenges in Design of Heterarchical Controls for Dynamic Logistic Systems	p. 3
1 Introduction	p. 3
2 Options for Structuring Controls for Logistic Systems	p. 6
2.1 Hierarchy	p. 7
2.2 Heterarchy	p. 7
2.3 Responsible Autonomy	p. 7
2.4 Anarchy	p. 7
3 Design of Heterarchical Control	p. 8
3.1 Principles for Partitioning	p. 9
3.2 Principles for Fault Tolerance	p. 9
3.3 Example: Heterarchical Control of Part Production	p. 9
3.4 Example: Heterarchical Control of a Multitude of Propulsion Units	p. 11
4 Developing and Evolving Organizations	p. 13
5 Design of Web Services	p. 17
6 Conclusions	p. 21
References	p. 23
Making the Business Case for RFID	p. 25
1 Introduction	p. 25
2 Model of RFID Assimilation	p. 26
2.1 Phase1: TechnologyDeployment	p. 27
2.2 Phase2: DataAnalytics	p. 27
2.3 Phase 3: Business Value - Proven	p. 29
2.4 Phase 3: Business Value - Potential	p. 32
3 Conclusion	p. 34
References	p. 34
General Aspects of Dynamics in Logistics
Review of Trends in Production and Logistic Networks and Supply Chain Evaluation	p. 39
1 Introduction	p. 39
2 From Supply Chain to Production Networks	p. 40
2.1 Supply Chain and Supply Chain Management	p. 40
2.2 Integration, Virtual Integration	p. 41
2.3 Joint Venture	p. 42
2.4 Cluster	p. 43
2.5 Production Networks	p. 43
2.6 Reverse Logistics	p. 43
2.7 Competence Profiling for Company Identification and Appraisal	p. 44
3 Performance Assessment of Supply Chains and Networks	p. 45
3.1 The Concept of Performance	p. 46
3.2 An Overall view of Performance Criteria	p. 47
3.3 Evaluation	p. 48
3.4 The Major role of Communication in an Assessment Process	p. 48
3.5 Real Time Networks Evaluation Technology: The Radio Frequency Identification (RFID)	p. 49
4 Established Benchmarks for Production Networks	p. 50
4.1 The Lean Principles in Supply	p. 50
4.2 The need for Agility	p. 51
4.3 Leagility	p. 51
5 Conclusions	p. 52
References	p. 52
Dynamic Data Mining for Improved Forecasting in Logistics and Supply Chain Management	p. 57
1 Introduction	p. 57
2 Support Vector Regression	p. 57
3 The Proposed Forecasting Methodology	p. 58
3.1 General Framework of the Proposed Methodology	p. 58
3.2 Model Updating within the Proposed Methodology	p. 59
4 Experiments and Results	p. 62
5 Conclusions and Future Works	p. 62
References	p. 63
Introducing Bounded Rationality into Self-Organization-Based Semiconductor Manufacturing	p. 65
1 Introduction	p. 65
2 Introducing Bounded-Rational Agents	p. 66
3 Self-Organization-Based Semiconductor Manufacturing Model	p. 67
3.1 Complexity of Semiconductor Manufacturing	p. 67
3.2 Self-Organization-Based Model	p. 68
3.3 Local Competitions in Self-Organization-Based System	p. 69
3.4 Introducing Spatial Restriction	p. 69
4 Simulation Results and Discussion	p. 70
4.1 Comparison Between Information Localization and Information-Use Limitation	p. 70
4.2 Introduction of Bounded Rationality	p. 72
5 Conclusion	p. 73
References	p. 73
Routing in Dynamic Logistics Networks
Travel Time Estimation and Deadlock-free Routing of an AGV System	p. 77
1 Introduction	p. 77
2 AGV Traffic Control	p. 78
2.1 Route Creation	p. 78
2.2 AGV Travel Scheduling	p. 79
3 Travel Time Estimation Algorithm	p. 80
3.1 Travel Time Estimation in Accelerated Motion	p. 80
3.2 Travel Time Estimation Considering Interference	p. 81
4 Experimental Results	p. 82
4.1 Experimental Setting	p. 82
4.2 Results	p. 82
5 Conclusions	p. 84
References	p. 84
Integration of Routing and Resource Allocation in Dynamic Logistic Networks	p. 85
1 Introduction	p. 85
2 Problem Description	p. 86
3 Mathematical Model	p. 87
4 Strategy for a Dynamic Environment	p. 90
5 Conclusion	p. 92
References	p. 92
Dynamic Vehicle Routing with Drivers' Working Hours	p. 95
1 Introduction	p. 95
2 Related Literature	p. 96
3 The General Vehicle Routing Problem	p. 96
4 Drivers' Working Hours	p. 97
5 Solution Approaches	p. 98
5.1 Reduced Variable Neighbourhood Search	p. 98
5.2 Large Neighbourhood Search	p. 99
6 Evaluation	p. 99
7 Conclusions	p. 101
References	p. 102
RFID in Logistics and Manufacturing Networks
A Survey of RFID Awareness and Use in the UK Logistics Industry	p. 105
1 Introduction	p. 105
1.1 Objectives	p. 106
1.2 Sample Selection	p. 106
2 Degree of Awareness of RFID	p. 108
3 RFID Adoption and Diffusion	p. 110
4 Modelling RFID Diffusion	p. 111
5 Barriers to RFID Adoption	p. 111
6 Conclusion	p. 114
References	p. 115
RFID-Based Intelligent Logistics for Distributed Production Networks	p. 117
1 Introduction	p. 117
2 Context-Driven Methodology	p. 118
3 Case Study	p. 120
4 Conclusion	p. 123
References	p. 124
Methodology for Development and Objective Comparison of Architectures for Networked RFID	p. 125
1 Introduction	p. 125
2 Problem Definition	p. 126
3 The Design Methodology	p. 127
4 Demonstrative Example	p. 128
4.1 General Ontology Definition	p. 128
4.2 Specific Ontology Definition	p. 129
4.3 Definition of Layers	p. 130
4.4 Usage of the Ontology Model	p. 130
5 Conclusions	p. 132
References	p. 132
Supply Chain Control Policies
Determining Optimal Control Policies for Supply Networks Under Uncertainty	p. 135
1 Introduction	p. 135
2 Optimal Control by Stochastic Dynamic Programming	p. 136
3 Numerical Example	p. 139
4 Conclusions	p. 140
References	p. 141
Adaptive Production and Inventory Control in Supply Chains against Changing Demand Uncertainty	p. 143
1 Introduction	p. 143
2 The production and inventory control policy	p. 144
3 Variance ratios and objective function	p. 145
4 Methodology	p. 146
5 Adaptive policy	p. 147
6 Summary	p. 150
References	p. 150
A Framework of Adaptive Control for Complex Production and Logistics Networks	p. 151
1 Introduction	p. 152
2 State-of-the-art	p. 152
3 Research methodology: MARINA	p. 153
4 Illustration	p. 155
5 Conclusions	p. 158
References	p. 159
Mechanisms of Instability in Small-Scale Manufacturing Networks	p. 161
1 Introduction	p. 161
2 Model Description	p. 162
3 Classification and Quantification of Instabilities	p. 164
4 Conclusions	p. 167
References	p. 168
Decentralized Decision-making in Supply Chains
Aspects of Agent Based Planning in the Demand Driven Railcab Scenario	p. 171
1 Introduction	p. 171
2 Problem Description	p. 172
3 Asynchronous Coordination and Synchronous Optimization	p. 173
4 Decentralized Optimization	p. 174
4.1 Decentralized Swapping of Jobs	p. 174
4.2 Decentralized Convoy Formation	p. 175
5 Consideration of Uncertain Travel Times	p. 176
6 Conclusion	p. 177
References	p. 177
Merging Time of Random Mobile Agents	p. 179
1 Introduction	p. 179
1.1 An Introductory Example	p. 181
2 A Genral Markov Chain Formulation	p. 182
2.1 Configurations Graph	p. 182
2.2 Components Graph	p. 183
2.3 From 2 to k Agents	p. 184
3 Hypercubes	p. 186
4 Conclusion and Perspectives	p. 189
References	p. 189
Dynamic Decision Making on Embedded Platforms in Transport Logistics - A Case Study	p. 191
1 Introduction	p. 191
2 Autonomous Decision Making in Transport Logistics	p. 192
3 Implementation in Embedded Systems	p. 193
3.1 Representation of Logistical Objects by Software Agents	p. 194
3.2 Interpretation of Sensor Data and Quality Assessment	p. 194
4 Distributed Solution of Route Planning Problems	p. 194
4.1 Distributed Planning by Truck Agents	p. 195
4.2 Experimental Evaluation	p. 196
5 Conclusion	p. 197
References	p. 197
The Global RF Lab Alliance: Research and Applications
The Value of RF Based Information	p. 201
1 Introduction	p. 201
2 Value of RF based information	p. 205
3 Solution Model - The "Billing Integrated Internet-of-Things"	p. 205
4 Business Scenarios	p. 207
5 Conclusion and future work	p. 209
References	p. 209
Reengineering and Simulation of an RFID Manufacturing System	p. 211
1 Introduction	p. 211
2 RFID Lab at the University of Parma	p. 212
3 Reengineeringand simulation of logistics processes	p. 213
4 Development of BIMs and results	p. 217
5 Future research directions and conclusions	p. 219
References	p. 219
LIT Middleware: Design and Implementation of RFID Middleware Based on the EPC Network Architecture	p. 221
1 Introduction	p. 221
2 Overview of EPC Network Architecture	p. 222
3 Features of LIT Middleware	p. 223
3.1 Features of ALE	p. 223
3.2 Features of EPCIS	p. 225
4 Design and Implementation of LIT Middleware	p. 226
5 Conclusions	p. 228
References	p. 229
Shelf Life Prediction by Intelligent RFID - Technical Limits of Model Accuracy	p. 231
1 Introduction	p. 231
2 Intelligent RFID as enabling technology	p. 232
3 Modelling approaches	p. 233
4 Software simulation for the table-shift approach	p. 234
5 Implementation	p. 235
5.1 Required resources	p. 236
6 Summary and outlook	p. 237
References	p. 238
Sustainable Collaboration
Effects of Autonomous Cooperation on the Robustness of International Supply Networks - Contributions and Limitations for the Management of External Dynamics in Complex Systems	p. 241
1 Risks of External Dynamics for the Robustness of Complex International Supply Networks	p. 241
2 Autonomous Cooperation as an Approach to Increase the Robustness of ISN	p. 243
3 Empirical Analysis	p. 244
4 Conclusions	p. 248
References	p. 248
Sustainability and Effectiveness in Global Supply Chains: Toward an Approach Based on a Long-term Learning Process	p. 251
1 Introduction	p. 251
2 Logistic Systems	p. 252
3 Logistic Systems' Potential Absorptive Capacity	p. 254
4 Preliminary Conclusions and Prospective Research	p. 256
References	p. 257
Risk Management in Dynamic Logistic Systems by Agent Based Autonomous Objects	p. 259
1 Introduction	p. 259
2 Complexity and Dynamic in Logistic Systems	p. 260
3 Control of a Dynamic System by Online Risk Management	p. 262
4 Risk Management of Autonomous Objects	p. 263
5 Technical Risk Aware Decision-Making	p. 264
6 Conclusion	p. 265
References	p. 266
Knowledge Management and Service Models in Logistics
Knowledge Management in Intermodal Logistics Networks	p. 269
1 Intermodallogistics networks	p. 269
2 Challenges in Knowledge Management	p. 270
3 Selected aspects of applied knowledge management in intermodallogistics	p. 272
4 Conclusions	p. 274
References	p. 274
Knowledge Management in Food Supply Chains	p. 277
1 Introduction	p. 277
2 Knowledge Management Processes	p. 278
3 Organizational Approach to Knowledge Management	p. 279
3.1 Learning Lab	p. 280
4 Conclusion	p. 282
References	p. 283
Service Models for a Small-sized Logistics Service Provider - A Case Study from Finland	p. 285
1 Introduction	p. 285
2 Service development steps	p. 288
3 Services for small sized LSP	p. 289
4 Conclusions	p. 290
References	p. 291
Container Logistics
A Framework for Integrating Planning Activities in Container Terminals	p. 295
1 Introduction	p. 295
2 The framework for a planning procedure	p. 296
3 Resource profiles for various activities	p. 298
4 Conclusion	p. 302
References	p. 303
Electronic Seals for Efficient Container Logistics	p. 305
1 Introduction	p. 305
2 Container Electronic Seals	p. 306
3 Cost-Effective Investments and Returns on ESeals	p. 307
4 Conclusions	p. 311
References	p. 312
Towards Autonomous Logistics: Conceptual, Spatial and Temporal Criteria for Container Cooperation	p. 313
1 Introduction	p. 313
2 Criteria for Cooperation	p. 314
2.1 Conceptual and Spatial Constraints	p. 315
2.2 Agent Clusters	p. 316
2.3 Temporal Constraints	p. 316
3 Case Study	p. 318
4 Discussion	p. 319
References	p. 320
Distributed Process Control by Smart Containers	p. 321
1 Introduction	p. 321
2 Problem	p. 322
3 Solution ideas	p. 323
4 Technical aspects	p. 323
5 Communicational aspects	p. 324
6 Modern Information processing	p. 326
7 Related work	p. 327
8 Future work	p. 328
References	p. 328
Autonomous Control in Logistics
Autonomous Units for Communication-based Dynamic Scheduling	p. 331
1 Introduction	p. 331
2 Autonomous Units	p. 332
3 Communication-based Dynamic Scheduling	p. 333
3.1 Transport Networks	p. 333
3.2 Sample Negotiation	p. 334
4 Conclusion	p. 337
References	p. 338
Autonomously Controlled Adaptation of Formal Decision Models - Comparison of Generic Approaches	p. 341
1 Introduction	p. 341
2 Vehicle Scheduling Problem	p. 341
3 Online Decision Strategies	p. 343
4 Numerical Experiments	p. 344
5 Conclusions	p. 348
References	p. 348
Clustering in Autonomous Cooperating Logistic Processes	p. 349
1 Introduction	p. 349
2 Routing and Clustering Approach	p. 350
3 Scenario Description	p. 351
3.1 Messages Sent during Clustering	p. 352
4 Communication Traffic for Clustering	p. 352
4.1 Representation and Assumption	p. 353
4.2 Messages Sent during Routing	p. 353
5 Results	p. 355
6 Summary and Outlook	p. 356
References	p. 357
Application of Small Gain Type Theorems in Logistics of Autonomous Processes	p. 359
1 Introduction	p. 359
2 Motivating example	p. 360
3 Feedback loop as a two nodes network	p. 361
3.1 Interpretations	p. 361
3.2 State equation and stability of the queues	p. 362
4 Conclusions	p. 364
References	p. 365
Appendix: Definitions and known results	p. 365
Next Generation Supply Chain Concepts
Web-service Based Integration of Multi-organizational Logistic Process	p. 369
1 Introduction	p. 369
2 Backgrounds	p. 370
2.1 Workflow interoperability	p. 370
2.2 XML and interoperability	p. 371
3 Web service and BPEL4WS	p. 372
3.1 Web service	p. 372
3.2 Process-oriented web service integration and BPEL4WS	p. 372
4 Workflow integration using BPEL4WS	p. 373
4.1 Using BPEL4WS as a process definition language	p. 373
4.2 Using BPEL4WS as a process exchange format	p. 375
4.3 Workflow as Web service	p. 376
4.4 Workflow as Web services' coordinator	p. 376
5 System implementation: uEngine	p. 377
6 Conclusions	p. 378
References	p. 379
An Approach for the Integration of Data Within Complex Logistics Systems	p. 381
1 Motivation	p. 381
2 Challenge	p. 383
3 State of the Art	p. 384
4 Approach to Data Integration	p. 385
5 Approach and Methodology	p. 387
6 Conclusion	p. 389
References	p. 389
Developing a Measurement Instrument for Supply Chain Event Management-Adoption	p. 391
1 Introduction	p. 391
2 Methodology	p. 392
2.1 Development of a measurement instrument for SCEM-adoption	p. 393
3 Implications	p. 400
4 Outlook	p. 402
References	p. 403
Developing a Security Event Management System for Intermodal Transport	p. 405
1 Introduction	p. 405
2 The SCEM approach	p. 406
3 Logistics Event Manager	p. 407
4 Security Event Manager	p. 408
4.1 Security related data and events	p. 408
4.2 Automatic messaging of events	p. 409
4.3 Generating events manually	p. 411
4.4 Security factor	p. 411
5 Conclusions	p. 412
References	p. 412
Logistic Processes Modelling
Autonomous Control of a Shop Floor Based on Bee's Foraging Behaviour	p. 415
1 Introduction	p. 415
2 Autonomy in production logistics	p. 416
3 Shop floor scenario	p. 416
4 Autonomous control based on bee's foraging behaviour	p. 417
4.1 Choosing the best feeding placein a honeybee colony	p. 417
4.2 Transfer of best feeding place choice to the best machining program problem	p. 418
5 Simulation Results	p. 419
5.1 Scenario without setup times	p. 419
5.2 Scenario with setup times	p. 421
6 Conclusion	p. 422
References	p. 422
Proof Principles of CSP - CSP-Prover in Practice	p. 425
1 Introduction	p. 425
2 The process algebra CSP in CSP-Prover	p. 427
3 Algebraic Laws	p. 429
3.1 Correctness proofs of algebraic laws	p. 430
3.2 Proofs based on algebraic laws	p. 432
4 Fixed point analysis	p. 433
4.1 Basic fixed point analysis techniques in CSP-Prover	p. 435
5 Deadlock analysis	p. 437
5.1 Proofs by abstraction	p. 438
6 Summary and Future work	p. 441
References	p. 442
Application of Markov Drift Processes to Logistical Systems Modeling	p. 443
1 Definition of Markov Drift Process and its Properties	p. 443
2 Production Line with Unreliable Units	p. 446
3 Interaction of Two Transport Units Via Warehouse	p. 448
4 Optimal Cargo-Flows Distribution among a Set of Transshipment Points	p. 451
5 Conclusion	p. 455
References	p. 455
Analysis of Decentral Order-picking Control Concepts	p. 457
1 Introduction	p. 457
2 Application	p. 458
3 Control strategies	p. 459
4 Experiments	p. 460
4.1 Evaluation	p. 460
4.2 Improvement by strategies	p. 463
5 Conclusion	p. 464
References	p. 464

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