Dong-Ping Song. Optimal Control and Optimization. of Stochastic. Supply Chain Systems. 4^ Springer
|
|
|
- Naomi Shepherd
- 10 years ago
- Views:
Transcription
1 Dong-Ping Song Optimal Control and Optimization Supply Chain Systems of Stochastic 4^ Springer
2 Contents 1 Stochastic Supply Chain Systems Introduction Uncertainties'in Supply Chain Systems Channel Relationships in Supply Chain Systems Optimal Control and Optimization in Stochastic Supply Chains Structure of the Book 6 References 8 2 Optimal Control of Basic Integrated Supply Chains Introduction Problem Formulation Optimal Control Policy Structural Properties of the Value Function Characterization of Optimal Policy Discussions Interpretation and Extension Information Sharing Channel Coordination Cost and Benefit Sharing Notes 32 References 33 3 Optimal Control of Supply Chains in More General Situations Introduction One Outstanding Order with Its Size Not Changeable Once Issued Two Outstanding Orders with Their Sizes Not Changeable Once Issued One Outstanding Order with Its Size Not Changeable and Its Lead Time Following an Erlang Distribution 44 XV
3 xvi Contents 3.5 Numerical Examples Multistage Serial Supply Chain Systems Discussions and Notes Deterministic Lead Times and Random Demands Stochastic Lead Times and Outstanding Orders Multiple Replenishment Channels and Order Information Ordering Capacity and Storage Capacity 56 References 57 4 Optimal Control of Supply Chain Systems with Backordering Decisions Introduction Optimal Control in a Supply Chain with Backordering Decisions Optimal Control in a Failure-Prone Manufacturing Supply Chain with Backordering Decisions Problem Formulation Optimal Control Policy Characterization of the Optimal Policy Discussions and Notes Backordering Decisions Failure-Prone Manufacturing Supply Chains 75 References 76 5 Optimal Control of Supply Chain Systems with Preventive Maintenance Decisions Introduction Optimal Control of Ordering, Production, and Preventive Maintenance in a Supply Chain Optimal Control Under Operation-Dependent Failures Optimal Control Under Time-Dependent Failures Optimal Control of Production and Preventive Maintenance in a Failure-Prone Manufacturing Supply Chain Discussion and Notes 90 References 93 6 Optimal Control of Supply Chain Systems with Assembly Operation Introduction Problem Formulation Optimal Control Policy Optimal Control Policy with Maximum Order Size One Structural Properties of Optimal Value Function Characterization of the Optimal Policy The Failure-Prone Assembly Supply Chain Discussion and Notes 108 References 109
4 Contents xvii 7 Optimal Control of Supply Chain Systems with Multiple Products.. Ill 7.1 Introduction Ill 7.2 Optimal Ordering and Production Control in a Supply Chain with Multiple Products Optimal Production Rate Allocation in a Failure-Prone Manufacturing Supply Chain Producing Two Part-Types Structural Properties of the Optimal Value Function Characterization of the Optimal Policy Discussion and Notes 125 References Threshold-Type Control Policies and System Stability for Serial Supply Chain Systems Introduction Stability Conditions and the Long-Run Average Cost Case Threshold Control Policies in the Basic Supply Chain System Threshold Control Policies in More General Supply Chain Systems Supply Chain Systems Subject to One Non-changeable Outstanding Order Supply Chain Systems with Two Parallel Outstanding Orders Supply Chain Systems Subject to Erlang Distributed Lead Times Numerical Examples in More General Supply Chain Systems Threshold Control Policy for Multistage Serial Supply Chains Discussion and Notes 146 References Threshold-Type Control of Supply Chain Systems with Backordering Decisions Introduction Threshold Control in the Basic Serial Supply Chain with Backordering Decisions Threshold Control in a Failure-Prone Manufacturing Supply Chain with Backordering Decisions System Stability and the Long-Run Average Cost Stationary Distribution Steady-State Performance Measures Numerical Examples Notes 160 References 160
5 xviii Contents 10 Threshold-Type Control of Supply Chain Systems with Preventive Maintenance Decisions System Stability Threshold-Type Control for Ordering, Production, and Preventive Maintenance in a Supply Chain Threshold-Type Control for Production and Preventive Maintenance in a Manufacturing Supply Chain Without Raw Material Ordering Activity State Transition Map Under Type-One Threshold Policy Stationary Distribution Under Type-One Threshold Policy Steady-State Performance Measures Numerical Examples Notes 182 References Threshold-Type Control of Supply Chain Systems with Assembly Operations System Stability Threshold Control Policies for Reliable Assembly Supply Chains Illustration of the Switching Structure of the Optimal Policy Threshold Control Policies Effectiveness of Threshold Control Policies Threshold Control Policies for Failure-Prone Assembly Supply Chains Illustration of the Switching Structure of the Optimal Policy Threshold Control Policies Effectiveness of Threshold Control Policies Notes 197 References Threshold-Type Control of Supply Chain Systems with Multiple Products System Stability ' Threshold-Type Control for Ordering and Production in a Supply Chain with Multiple Products Threshold-Type Control for Production Rate Allocation in a Failure-Prone Manufacturing Supply Chain with Two Part-Types Prioritized Base-Stock Threshold Control for a Manufacturing Supply Chain Producing Two Part-Types with Given Priority System Stability 209
6 Contents xix Stationary Distribution Steady-State Performance Measures Optimal Base-Stock Levels Numerical Examples Discussion and Notes 222 References Optimization of Threshold Control Parameters via Numerical Methods Introduction Optimization of Threshold Parameters in Discounted- Cost Situations Optimization of Threshold Values via Value Iteration Method Application and Computational Performance Optimization of Threshold Parameters in Long-Run Average Cost Situations Optimization of Threshold Parameters via Value Iteration Method Optimization of Threshold Parameters via Stationary Distribution Application and Computational Performance Robustness of Threshold-Type Control Policies Discussion and Notes 235 References Optimization of Threshold Control Parameters via Simulation-Based Methods Introduction Performance Evaluation Through an Event-Driven Simulation Model Simulation-Based Optimization Methods Genetic Algorithms (Evolutionary Strategy) Simulated Annealing Numerical Examples Ordinal Optimization Technique The Concept of Ordinal Optimization An OO-Based Elite GA Notes 256 References Conclusions Conclusions and Managerial Insights Limitations and Further Research 263 References 265 Index 267
A QUEUEING-INVENTORY SYSTEM WITH DEFECTIVE ITEMS AND POISSON DEMAND. [email protected]
A QUEUEING-INVENTORY SYSTEM WITH DEFECTIVE ITEMS AND POISSON DEMAND Rasoul Hai 1, Babak Hai 1 Industrial Engineering Department, Sharif University of Technology, +98-1-66165708, [email protected] Industrial
Planning and Scheduling in Manufacturing and Services
Michael L. Pinedo Planning and Scheduling in Manufacturing and Services Second edition 4y Springer Preface Contents of CD-ROM vii xvii Part I Preliminaries 1 Introduction 3 1.1 Planning and Scheduling:
Managing Supply Chain Risk
ManMohan S. Sodhi Christopher S. Tang Managing Supply Chain Risk ^J Springer Contents Foreword Endorsements Acknowledgements ix xi xiii Part I Introduction Identifying, Assessing, Mitigating and Responding
Inventory Control with Risk of Major Supply Chain Disruptions. Brian M. Lewis
Inventory Control with Risk of Major Supply Chain Disruptions A Thesis Presented to The Academic Faculty by Brian M. Lewis In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
Springer SUPPLY CHAIN CONFIGURATION CONCEPTS, SOLUTIONS, AND APPLICATIONS. Cham Chandra University of Michigan - Dearborn Dearborn, Michigan, USA
SUPPLY CHAIN CONFIGURATION CONCEPTS, SOLUTIONS, AND APPLICATIONS Cham Chandra University of Michigan - Dearborn Dearborn, Michigan, USA Jänis Grabis Riga Technical University Riga, Latvia Springer Contents
William E. Hart Carl Laird Jean-Paul Watson David L. Woodruff. Pyomo Optimization. Modeling in Python. ^ Springer
William E Hart Carl Laird Jean-Paul Watson David L Woodruff Pyomo Optimization Modeling in Python ^ Springer Contents 1 Introduction 1 11 Mathematical Modeling 1 12 Modeling Languages for Optimization
Network Security A Decision and Game-Theoretic Approach
Network Security A Decision and Game-Theoretic Approach Tansu Alpcan Deutsche Telekom Laboratories, Technical University of Berlin, Germany and Tamer Ba ar University of Illinois at Urbana-Champaign, USA
A Programme Implementation of Several Inventory Control Algorithms
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume, No Sofia 20 A Programme Implementation of Several Inventory Control Algorithms Vladimir Monov, Tasho Tashev Institute of Information
Approximation Algorithms for Stochastic Inventory Control Models
Approximation Algorithms for Stochastic Inventory Control Models (Abstract) Retsef Levi Martin Pál Robin O. Roundy David B. Shmoys School of ORIE, Cornell University, Ithaca, NY 14853, USA DIMACS Center,
INTEGRATED OPTIMIZATION OF SAFETY STOCK
INTEGRATED OPTIMIZATION OF SAFETY STOCK AND TRANSPORTATION CAPACITY Horst Tempelmeier Department of Production Management University of Cologne Albertus-Magnus-Platz D-50932 Koeln, Germany http://www.spw.uni-koeln.de/
Comparison of periodic-review inventory control policies. in a serial supply chain
025-0998 Comparison of periodic-review inventory control policies in a serial supply chain Nihan Kabadayi, İstanbul University, Faculty of Business Administration, Production Management Department, Avcılar,
Retail Category Management
Alexander Hiibner Retail Category Management Decision Support Systems for Assortment, Shelf Space, Inventory and Price Planning fyj. Springer Contents 1 Outline 1 1.1 Background and Motivation 1 1.2 Objectives
Project Management with Dynamic Scheduling
Mario Vanhoucke Project Management with Dynamic Scheduling Baseline Scheduling, Risk Analysis and Project Control 4u Springer 1 Introduction 1 1.1 Introduction 1 1.2 The Project Life Cycle (PLC) 2 1.2.1
Companies often face nonstationary demand due to product life cycles and seasonality, and nonstationary
MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol. 14, No. 3, Summer 2012, pp. 414 422 ISSN 1523-4614 (print) ISSN 1526-5498 (online) http://dx.doi.org/10.1287/msom.1110.0373 2012 INFORMS Single-Stage
Mario Vanhoucke. Project Management. with Dynamic Scheduling. Baseline Scheduling, Risk Analysis. and Project Control. Second Edition.
Mario Vanhoucke Project Management with Dynamic Scheduling Baseline Scheduling, Risk Analysis and Project Control Second Edition 4^ Springer Contents 1 Introduction 1 1.1 Introduction 1 1.2 The Project
THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS
Contents Preface xv 1. ROBOTIC CELLS IN PRACTICE 1 1.1 Cellular Manufacturing 2 1.2 Robotic Cell Flowshops 3 1.3 Throughput Optimization 7 1.4 Historical Overview 9 1.5 Applications 11 2. A CLASSIFICATION
The Stationary Beer Game
The Stationary Beer Game Fangruo Chen and Rungson Samroengraja Graduate School of Business, Columbia University, New York, NY 127 Phone: 212-854-8694 Fax: 212-316-918 Booz, Allen & Hamilton Inc., 11 Park
UNCERTAINTY IN THE ELECTRIC POWER INDUSTRY Methods and Models for Decision Support
UNCERTAINTY IN THE ELECTRIC POWER INDUSTRY Methods and Models for Decision Support CHRISTOPH WEBER University of Stuttgart, Institute for Energy Economics and Rational of Use of Energy fyj. Springer Contents
Regression Modeling Strategies
Frank E. Harrell, Jr. Regression Modeling Strategies With Applications to Linear Models, Logistic Regression, and Survival Analysis With 141 Figures Springer Contents Preface Typographical Conventions
Alessandro Birolini. ineerin. Theory and Practice. Fifth edition. With 140 Figures, 60 Tables, 120 Examples, and 50 Problems.
Alessandro Birolini Re ia i it En ineerin Theory and Practice Fifth edition With 140 Figures, 60 Tables, 120 Examples, and 50 Problems ~ Springer Contents 1 Basic Concepts, Quality and Reliability Assurance
Issues in inventory control models with demand and supply uncertainty Thesis proposal
Issues in inventory control models with demand and supply uncertainty Thesis proposal Abhijit B. Bendre August 8, 2008 CORAL Centre for Operations Research Applications in Logistics Dept. of Business Studies,
Manufacturing Systems Modeling and Analysis
Guy L. Curry Richard M. Feldman Manufacturing Systems Modeling and Analysis 4y Springer 1 Basic Probability Review 1 1.1 Basic Definitions 1 1.2 Random Variables and Distribution Functions 4 1.3 Mean and
SPARE PARTS INVENTORY SYSTEMS UNDER AN INCREASING FAILURE RATE DEMAND INTERVAL DISTRIBUTION
SPARE PARS INVENORY SYSEMS UNDER AN INCREASING FAILURE RAE DEMAND INERVAL DISRIBUION Safa Saidane 1, M. Zied Babai 2, M. Salah Aguir 3, Ouajdi Korbaa 4 1 National School of Computer Sciences (unisia),
Univariate and Multivariate Methods PEARSON. Addison Wesley
Time Series Analysis Univariate and Multivariate Methods SECOND EDITION William W. S. Wei Department of Statistics The Fox School of Business and Management Temple University PEARSON Addison Wesley Boston
1 of 7 31/10/2012 18:34
Regulatory Story Go to market news section Company TIDM Headline Released Number Ironveld PLC IRON Holding(s) in Company 18:01 31-Oct-2012 0348Q18 RNS Number : 0348Q Ironveld PLC 31 October 2012 TR-1:
Adaptive Variable Step Size in LMS Algorithm Using Evolutionary Programming: VSSLMSEV
Adaptive Variable Step Size in LMS Algorithm Using Evolutionary Programming: VSSLMSEV Ajjaiah H.B.M Research scholar Jyothi institute of Technology Bangalore, 560006, India Prabhakar V Hunagund Dept.of
Introduction to Natural Computation. Lecture 15. Fruitflies for Frequency Assignment. Alberto Moraglio
Introduction to Natural Computation Lecture 15 Fruitflies for Frequency Assignment Alberto Moraglio 1/39 Fruit flies 2/39 Overview of the Lecture The problem of frequency assignment in mobile phone networks.
The life cycle of new products is becoming shorter and shorter in all markets. For electronic products, life
MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol. 10, No. 2, Spring 2008, pp. 278 287 issn 1523-4614 eissn 1526-5498 08 1002 0278 informs doi 10.1287/msom.1070.0175 2008 INFORMS Strategic Inventory Placement
Lecture. Simulation and optimization
Course Simulation Lecture Simulation and optimization 1 4/3/2015 Simulation and optimization Platform busses at Schiphol Optimization: Find a feasible assignment of bus trips to bus shifts (driver and
D A T A M I N I N G C L A S S I F I C A T I O N
D A T A M I N I N G C L A S S I F I C A T I O N FABRICIO VOZNIKA LEO NARDO VIA NA INTRODUCTION Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe.
Revenue Management and Survival Analysis in the Automobile Industry
Andre Jerenz Revenue Management and Survival Analysis in the Automobile Industry With a foreword by Prof. Dr. Ulrich Tushaus GABLER EDITION WISSENSCHAFT List of Figures List of Tables Nomenclature xiii
Practical Applications of Evolutionary Computation to Financial Engineering
Hitoshi Iba and Claus C. Aranha Practical Applications of Evolutionary Computation to Financial Engineering Robust Techniques for Forecasting, Trading and Hedging 4Q Springer Contents 1 Introduction to
Introduction. Chapter 1
Chapter 1 Introduction The success of Japanese companies in the second half of the 20th century has lead to an increased interest in inventory management. Typically, these companies operated with far less
A Profit-Maximizing Production Lot sizing Decision Model with Stochastic Demand
A Profit-Maximizing Production Lot sizing Decision Model with Stochastic Demand Kizito Paul Mubiru Department of Mechanical and Production Engineering Kyambogo University, Uganda Abstract - Demand uncertainty
Optimal base-stock policy for the inventory system with periodic review, backorders and sequential lead times
44 Int. J. Inventory Research, Vol. 1, No. 1, 2008 Optimal base-stock policy for the inventory system with periodic review, backorders and sequential lead times Søren Glud Johansen Department of Operations
Integer Programming: Algorithms - 3
Week 9 Integer Programming: Algorithms - 3 OPR 992 Applied Mathematical Programming OPR 992 - Applied Mathematical Programming - p. 1/12 Dantzig-Wolfe Reformulation Example Strength of the Linear Programming
STRATEGIC CAPACITY PLANNING USING STOCK CONTROL MODEL
Session 6. Applications of Mathematical Methods to Logistics and Business Proceedings of the 9th International Conference Reliability and Statistics in Transportation and Communication (RelStat 09), 21
Optimizing Replenishment Intervals for Two-Echelon Distribution Systems with Fixed Order Costs
Optimizing Replenishment Intervals for Two-Echelon Distribution Systems with Fixed Order Costs Kevin H. Shang Sean X. Zhou Fuqua School of Business, Duke University, Durham, North Carolina 27708, USA Systems
FIXED CHARGE UNBALANCED TRANSPORTATION PROBLEM IN INVENTORY POOLING WITH MULTIPLE RETAILERS
FIXED CHARGE UNBALANCED TRANSPORTATION PROBLEM IN INVENTORY POOLING WITH MULTIPLE RETAILERS Ramidayu Yousuk Faculty of Engineering, Kasetsart University, Bangkok, Thailand [email protected] Huynh Trung
Optimal Dynamic Resource Allocation in Multi-Class Queueing Networks
Imperial College London Department of Computing Optimal Dynamic Resource Allocation in Multi-Class Queueing Networks MEng Individual Project Report Diagoras Nicolaides Supervisor: Dr William Knottenbelt
Forecasting and Hedging in the Foreign Exchange Markets
Christian Ullrich Forecasting and Hedging in the Foreign Exchange Markets 4u Springer Contents Part I Introduction 1 Motivation 3 2 Analytical Outlook 7 2.1 Foreign Exchange Market Predictability 7 2.2
DR. BABASAHEB AMBEDKAR MARATHWADA UNIVERSITY, AURANGABAD. PROGRAMME
BCA 1 DR BABASAHEB AMBEDKAR MARATHWADA UNIVERSITY, AURANGABAD Diploma in Business Management Semester I st & II nd Semester (New Syllabus 60/40) Examination May-2011 The Examination held on the Days and
An Inventory Model with Recovery and Environment Considerations
An Inventory Model with Recovery and Environment Considerations Marthy S. García-Alvarado Marc Paquet Amin Chaabane January 2014 CIRRELT-2014-03 Marthy S. García-Alvarado 1,2,*, Marc Paquet 1,2, Amin Chaabane
Applied mathematics and mathematical statistics
Applied mathematics and mathematical statistics The graduate school is organised within the Department of Mathematical Sciences.. Deputy head of department: Aila Särkkä Director of Graduate Studies: Marija
Chapter 1. Introduction
Chapter 1 Introduction 1.1. Motivation Network performance analysis, and the underlying queueing theory, was born at the beginning of the 20th Century when two Scandinavian engineers, Erlang 1 and Engset
Regulatory Story. RNS Number : 8343I. DCD Media PLC. 08 July 2013. TR-1: NOTIFICATION OF MAJOR INTEREST IN SHARES i
1 of 7 25/11/2013 11:51 Regulatory Story Go to market news section Company TIDM Headline Released DCD Media PLC DCD Holding(s) in Company 15:19 08-Jul-2013 8343I15 RNS : 8343I DCD Media PLC 08 July 2013
Economic Production Quantity (EPQ) Model with Time- Dependent Demand and Reduction Delivery Policy
ISSN NO:: 348 537X Economic Production Quantity (EPQ) Model with Time- Dependent Demand and Reduction Delivery Policy Dr. Neeraj Agarwal Professor & Head, Department of Hotel Management, Graphic Era University,
General lotsizing problem in a closed-loop supply chain with uncertain returns
General lotsizing problem in a closed-loop supply chain with uncertain returns Guillaume Amand, Yasemin Arda July 3, 2013 G. Amand and Y. Arda (HEC-Ulg) General lotsizing problem in a closed-loop supply
We consider the optimal production and inventory control of an assemble-to-order system with m components,
MANAGEMENT SCIENCE Vol. 52, No. 12, December 2006, pp. 1896 1912 issn 0025-1909 eissn 1526-5501 06 5212 1896 informs doi 10.1287/mnsc.1060.0588 2006 INFORMS Production and Inventory Control of a Single
Agenda. Real System, Transactional IT, Analytic IT. What s the Supply Chain. Levels of Decision Making. Supply Chain Optimization
Agenda Supply Chain Optimization KUBO Mikio Definition of the Supply Chain (SC) and Logistics Decision Levels of the SC Classification of Basic Models in the SC Logistics Network Design Production Planning
Performance Optimization of I-4 I 4 Gasoline Engine with Variable Valve Timing Using WAVE/iSIGHT
Performance Optimization of I-4 I 4 Gasoline Engine with Variable Valve Timing Using WAVE/iSIGHT Sean Li, DaimlerChrysler (sl60@dcx dcx.com) Charles Yuan, Engineous Software, Inc ([email protected]) Background!
Supplement to Call Centers with Delay Information: Models and Insights
Supplement to Call Centers with Delay Information: Models and Insights Oualid Jouini 1 Zeynep Akşin 2 Yves Dallery 1 1 Laboratoire Genie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92290
Supply Chain Management on Demand
Chae An Hansjorg Fromm (Eds.) Supply Chain Management on Demand Strategies, Technologies, Applications With contributions by numerous experts With 87 Figures 4y Springer Technische Universitat Darmstadt
Probability and Statistics
Probability and Statistics Syllabus for the TEMPUS SEE PhD Course (Podgorica, April 4 29, 2011) Franz Kappel 1 Institute for Mathematics and Scientific Computing University of Graz Žaneta Popeska 2 Faculty
Inventory Management: Fundamental Concepts & EOQ. Chris Caplice ESD.260/15.770/1.260 Logistics Systems Oct 2006
Inventory Management: Fundamental Concepts & EOQ Chris Caplice ESD.260/15.770/1.260 Logistics Systems Oct 2006 Agenda Wrap up of Demand Forecasting Fundamentals of Inventory Management Economic Order Quantity
Single item inventory control under periodic review and a minimum order quantity
Single item inventory control under periodic review and a minimum order quantity G. P. Kiesmüller, A.G. de Kok, S. Dabia Faculty of Technology Management, Technische Universiteit Eindhoven, P.O. Box 513,
A Genetic Algorithm Approach for Solving a Flexible Job Shop Scheduling Problem
A Genetic Algorithm Approach for Solving a Flexible Job Shop Scheduling Problem Sayedmohammadreza Vaghefinezhad 1, Kuan Yew Wong 2 1 Department of Manufacturing & Industrial Engineering, Faculty of Mechanical
Optimal Tuning of PID Controller Using Meta Heuristic Approach
International Journal of Electronic and Electrical Engineering. ISSN 0974-2174, Volume 7, Number 2 (2014), pp. 171-176 International Research Publication House http://www.irphouse.com Optimal Tuning of
Holger Dannenberg Dirk Zupancic. Optimising Customer and Sales Management
Holger Dannenberg Dirk Zupancic Optimising Customer and Sales Management Contents Preface I. Preface II V IX Foreword, XIII Profile of the authors XV 1. Introduction: Excellence in sales and customer management..;..'
Research Article Two-Period Inventory Control with Manufacturing and Remanufacturing under Return Compensation Policy
Discrete Dynamics in Nature and Society Volume 2013, Article ID 871286, 8 pages http://dx.doi.org/10.1155/2013/871286 Research Article Two-Period Inventory Control with Manufacturing and Remanufacturing
Multi-Objective Genetic Test Generation for Systems-on-Chip Hardware Verification
Multi-Objective Genetic Test Generation for Systems-on-Chip Hardware Verification Adriel Cheng Cheng-Chew Lim The University of Adelaide, Australia 5005 Abstract We propose a test generation method employing
The Lecture Contains: Application of stochastic processes in areas like manufacturing. Product(s)/Good(s) to be produced. Decision variables
The Lecture Contains: Application of stochastic processes in areas like manufacturing Product(s)/Good(s) to be produced Decision variables Structure of decision problem Demand Ordering/Production Cost
Stephane Crepey. Financial Modeling. A Backward Stochastic Differential Equations Perspective. 4y Springer
Stephane Crepey Financial Modeling A Backward Stochastic Differential Equations Perspective 4y Springer Part I An Introductory Course in Stochastic Processes 1 Some Classes of Discrete-Time Stochastic
Supply Chain Management and Advanced Planning
Christoph Kilger Editors Supply Chain Management and Advanced Planning Concepts, Models, Software, and Case Studies 4th Edition 4y Springer Contents Preface, Christoph Kilger V Introduction 1 References
Chapter 1 Introduction to Inventory Replenishment Planning
Chapter 1 Introduction to Inventory Replenishment Planning Chapter Contents OVERVIEW... 7 IMPACT OF INVENTORY... 7 FUNCTION OF INVENTORY... 8 SUMMARY OF FUNCTIONALITY... 9 REFERENCES... 10 6 Chapter 1.
Spare Parts Inventory Model for Auto Mobile Sector Using Genetic Algorithm
Parts Inventory Model for Auto Mobile Sector Using Genetic Algorithm S. Godwin Barnabas, I. Ambrose Edward, and S.Thandeeswaran Abstract In this paper the objective is to determine the optimal allocation
Iman Ziari. M.Sc, B.Eng (Electrical Engineering) A Thesis submitted in Partial Fulfillment of the Requirement for the Degree of. Doctor of Philosophy
Planning of Distribution Networks for Medium Voltage and Low Voltage Iman Ziari M.Sc, B.Eng (Electrical Engineering) A Thesis submitted in Partial Fulfillment of the Requirement for the Degree of Doctor
Empirically Identifying the Best Genetic Algorithm for Covering Array Generation
Empirically Identifying the Best Genetic Algorithm for Covering Array Generation Liang Yalan 1, Changhai Nie 1, Jonathan M. Kauffman 2, Gregory M. Kapfhammer 2, Hareton Leung 3 1 Department of Computer
Process Mining. ^J Springer. Discovery, Conformance and Enhancement of Business Processes. Wil M.R van der Aalst Q UNIVERS1TAT.
Wil M.R van der Aalst Process Mining Discovery, Conformance and Enhancement of Business Processes Q UNIVERS1TAT m LIECHTENSTEIN Bibliothek ^J Springer Contents 1 Introduction I 1.1 Data Explosion I 1.2
MODELING & SIMULATION IN BUSINESS PROCESS MANAGEMENT
MODELING & SIMULATION IN BUSINESS PROCESS MANAGEMENT M. W. Barnett Director of Professional Services Gensym Corporation SIMULATION AND BUSINESS PROCESS CHANGE Simulation is a tool for managing change.
Biopharmaceutical Portfolio Management Optimization under Uncertainty
Ian David Lockhart Bogle and Michael Fairweather (Editors), Proceedings of the 22nd European Symposium on Computer Aided Process Engineering, 17-20 June 2012, London. 2012 Elsevier B.V. All rights reserved
ARIS Design Platform Getting Started with BPM
Rob Davis and Eric Brabander ARIS Design Platform Getting Started with BPM 4y Springer Contents Acknowledgements Foreword xvii xix Chapter 1 An Introduction to BPM 1 1.1 Brief History of Business Process
Software and Hardware Solutions for Accurate Data and Profitable Operations. Miguel J. Donald J. Chmielewski Contributor. DuyQuang Nguyen Tanth
Smart Process Plants Software and Hardware Solutions for Accurate Data and Profitable Operations Miguel J. Bagajewicz, Ph.D. University of Oklahoma Donald J. Chmielewski Contributor DuyQuang Nguyen Tanth
Keywords revenue management, yield management, genetic algorithm, airline reservation
Volume 4, Issue 1, January 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Revenue Management
Web based Multi Product Inventory Optimization using Genetic Algorithm
Web based Multi Product Inventory Optimization using Genetic Algorithm Priya P Research Scholar, Dept of computer science, Bharathiar University, Coimbatore Dr.K.Iyakutti Senior Professor, Madurai Kamarajar
Simulation-based traffic management for autonomous and connected vehicles
Simulation-based traffic management for autonomous and connected vehicles Paweł Gora Faculty of Mathematics, Informatics and Mechanics University of Warsaw ITS Kraków, 3-4.12.2015 Axioms Vehicles may communicate
Genetic algorithms for changing environments
Genetic algorithms for changing environments John J. Grefenstette Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 375, USA [email protected] Abstract
OPTIMAL STOPPING PROBLEMS IN OPERATIONS MANAGEMENT
OPTIMAL STOPPING PROBLEMS IN OPERATIONS MANAGEMENT A DISSERTATION SUBMITTED TO THE DEPARTMENT OF MANAGEMENT SCIENCE AND ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL
Spreadsheet Heuristic for Stochastic Demand Environments to Solve the Joint Replenishment Problem
, July 3-5, 2013, London, U.K. Spreadsheet Heuristic for Stochastic Demand Environments to Solve the Joint Replenishment Problem Buket Türkay, S. Emre Alptekin Abstract In this paper, a new adaptation
