Ch.01 Introduction to Modeling. Management Science / Instructor: Bonghyun Ahn
|
|
- Adela Caldwell
- 6 years ago
- Views:
Transcription
1 Ch.01 Introduction to Modeling Management Science / Instructor: Bonghyun Ahn
2 Chapter Topics The Management Science Approach to Problem Solving Model Building: Break-Even Analysis Computer Solution Management Science Modeling Techniques Business Usage of Management Science Techniques Management Science Models in Decision Support Systems 2
3 The Management Science Approach Management science is a scientific approach to solving management problems. It is used in a variety of organizations to solve many different types of problems. It encompasses a logical mathematical approach to problem solving. Management science, also known as operations research, quantitative methods, etc., involves a philosophy of problem solving in a logical manner. 3
4 The Management Science Process Observation - Identification of a problem that exists (or may occur soon) in a system or organization Definition of the Problem - problem must be clearly and consistently defined, showing its boundaries and interactions with the objectives of the organization Model Construction - Development of the functional mathematical relationships that describe the decision variables, objective function and constraints of the problem Model Solution - Models solved using management science techniques Model Implementation - Actual use of the model or its solution 4
5 Example of Model Construction (1 of 3) Information and Data: - Business firm makes and sells a steel product - Product costs $5 to produce - Product sells for $20 - Product requires 4 pounds of steel to make - Firm has 100 pounds of steel Business Problem: - Determine the number of units to produce to make the most profit, given the limited amount of steel available. 5
6 Example of Model Construction (2 of 3) Variables: x = # units to produce (decision variable) Z = total profit (in $) Model: Z = $20x - $5x (objective function) 4x = 100 lb. of steel (resource constraint) Parameters: $20, $5, 4 lbs, 100 lbs (known values) Formal Specification of Model: maximize Z = $20x - $5x subject to 4x = 100 6
7 Example of Model Construction (3 of 3) Model Solution: Solve the constraint equation: 4x = 100 (4x)/4 = (100)/4 x = 25 units Substitute this value into the profit function: Z = $20x - $5x = (20)(25) (5)(25) = $375 (Produce 25 units, to yield a profit of $375) 7
8 Model Building: Break-Even Analysis (1 of 6) Used to determine the number of units of a product to sell or produce that will equate total revenue with total cost. The volume at which total revenue equals total cost is called the break-even point. Profit at break-even point is zero. 8
9 Model Building: Break-Even Analysis (2 of 6) Model Components - Fixed Cost (c f ) - costs that remain constant regardless of number of units produced. - Variable Cost (c v ) - unit production cost of product. - Volume (v) the number of units produced or sold - Total variable cost (vc v ) - function of volume (v) and unit variable cost. - Total Cost (TC) - total fixed cost plus total variable cost. TC = c f + vc v - Profit (Z) - difference between total revenue vp (p = unit price) and total cost, i.e. Z = vp - c - vc f v 9
10 Model Building: Break-Even Analysis (3 of 6) Computing the Break-Even Point - The break-even point is that volume at which total revenue equals total cost and profit is zero: vp v( - p c - f c v - ) vc = v c f = 0 - The break-even point v = c f p - c v 10
11 Model Building: Break-Even Analysis (4 of 6) Example: Western Clothing Company Fixed Costs: c f = $10000 Variable Costs: c v = $8 per pair Price : p = $23 per pair The Break-Even Point is: v = (10,000)/(23-8) = pairs 11
12 Model Building: Break-Even Analysis (5 of 6) Figure 1.2 Breakeven model Figure 1.3 Breakeven model with an increase in price 12
13 Model Building: Break-Even Analysis (6 of 6) Figure 1.4 Breakeven model with an increase in variable cost Figure 1.5 Breakeven model with a change in fixed cost 13
14 Break-Even Analysis: Excel Solution (1 of 4) Formula for v, break-even point, =D4/(D8-D6) Exhibit
15 Break-Even Analysis: Excel Solution (2 of 4) Click on Add- Ins, then the menu of Excel QM modules Enter model parameters in cells B10:B13 Exhibit
16 Break-Even Analysis: Excel Solution (3 of 4) Exhibit
17 Break-Even Analysis: Excel Solution (4 of 4) Exhibit
18 Classification of Management Science Techniques Management Science techniques Text Linear mathematical programming Linear programming models Graphical analysis Sensitivity analysis Transportation, transportation, transshipment, and assignment Integer linear programming Goal programming Probabilistic techniques Network techniques Other techniques Companion web site Probability and statistics Decision analysis Queuing Network flow Project management (PERT/CPM) Analytical hierarchy process (AHP) Nonlinear programming Simulation Forecasting Inventory Simplex method Transportation and assignment methods Nonlinear programming Game theory Markov analysis Branch and bound method 18
19 Characteristics of Modeling Techniques Linear Mathematical Programming Techniques - clear objective; restrictions on resources and requirements; parameters known with certainty. (Chap 2-6, 9) Probabilistic Techniques - results contain uncertainty. (Chap 11-13) Network Techniques - model often formulated as diagram; deterministic or probabilistic. (Chap 7-8) Other Techniques - variety of deterministic and probabilistic methods for specific types of problems including forecasting, inventory, simulation, multicriteria, AHP (analytic hierarchy process), etc. (Chap 9, 14-16) 19
20 Business Usage of Management Science Some application areas: - Project Planning - Capital Budgeting - Inventory Analysis - Production Planning - Scheduling Interfaces - Applications journal published by Institute for Operations Research and Management Sciences (INFORMS) 20
21 Management Science Models in DSS (1 of 2) A Decision Support System(DSS) is a computer-based system that helps decision makers address complex problems that cut across different parts of an organization and operations. - Features of Decision Support Systems Interactive Uses databases & management science models Address what if questions Perform sensitivity analysis - Examples include: ERP Enterprise Resource Planning OLAP Online Analytical Processing 21
22 Management Science Models in DSS (2 of 2) Figure 1.7 Decision Support System 22
Chapter 9. Building Model-Driven Decision Support Systems
. Chapter 9 Building Model-Driven Decision Support Systems Models can help us understand business problems and help us make decisions. Introduction Many companies use models to assist managers. For example,
More informationPresentation: H. Sarper An Introduction to Modeling
Chapter 1 An introduction to Model Building to accompany Introduction to Mathematical Programming: Operations Research, Volume 1 4th edition, by Wayne L. Winston and Munirpallam Venkataramanan Presentation:
More informationSTATE UNIVERSITY OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK COURSE OUTLINE ECON 314- MANAGERIAL ECONOMICS. Prepared by: Karen Spellacy
STATE UNIVERSITY OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK COURSE OUTLINE ECON 314- MANAGERIAL ECONOMICS Prepared by: Karen Spellacy Updated by Edouard Mafoua SCHOOL OF BUSINESS AND LIBERAL ARTS
More informationMULTI CRITERIA EVALUATION
MULTI CRITERIA EVALUATION OVERVIEW Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives.
More information(Assignment) Master of Business Administration (MBA) PGDPM Subject : Management Subject Code : PGDPM
(Assignment) 2017-2018 Master of Business Administration (MBA) PGDPM Subject : Management Subject Code : PGDPM Subject Title : Operation Research Course Code : PGDPM-01 Maximum Marks: 30 Note: Long Answer
More informationQUANTITATIVE MODULE Quantitative Decision- Making Aids
2 QUANTITATIVE MODULE Quantitative Decision- Making Aids In this module, we ll look at several decision-making aids and techniques, as well as some popular tools for managing projects. 1 Specifically we
More informationOutline. Advanced Herd Management Course introduction. Brush-up courses. Preconditions
Outline Advanced Herd Management Course introduction Anders Ringgaard Kristensen Preconditions Outcome: What are you supposed to learn? The framework and definition of herd management The management cycle
More informationChapter 4. Models for Known Demand
Chapter 4 Models for Known Demand Introduction EOQ analysis is based on a number of assumptions. In the next two chapters we describe some models where these assumptions are removed. This chapter keeps
More informationTechniques of Operations Research
Techniques of Operations Research C HAPTER 2 2.1 INTRODUCTION The term, Operations Research was first coined in 1940 by McClosky and Trefthen in a small town called Bowdsey of the United Kingdom. This
More informationLinear Programming and Applications
Linear Programming and Applications (v) LP Applications: Water Resources Problems Objectives To formulate LP problems To discuss the applications of LP in Deciding the optimal pattern of irrigation Water
More informationWhite Paper. Demand Shaping. Achieving and Maintaining Optimal Supply-and-Demand Alignment
White Paper Demand Shaping Achieving and Maintaining Optimal Supply-and-Demand Alignment Contents Introduction... 1 Sense-Interpret-Respond Architecture... 2 Sales and Operations Planning... 3 Scenario
More informationExcel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray)
Gebauer/Matthews: MIS 213 Hands-on Tutorials and Cases, Spring 2015 111 Excel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray) Purpose: Using Excel Solver as a Decision Support
More informationThe Training Material on Logistics Planning and Analysis has been produced under Project Sustainable Human Resource Development in Logistic Services
The Training Material on Logistics Planning and Analysis has been produced under Project Sustainable Human Resource Development in Logistic Services for ASEAN Member States with the support from Japan-ASEAN
More informationERP Reference models and module implementation
ERP Reference models and module implementation Based on Supporting the module sequencing decision in the ERP implementation process An application of the ANP method, Petri Hallikainen, Hannu Kivijärvi
More informationElasticity and Its Applications. Copyright 2004 South-Western
Elasticity and Its Applications 5 Copyright 2004 South-Western Copyright 2004 South-Western/Thomson Learning Elasticity... allows us to analyze supply and demand with greater precision. is a measure of
More informationLicensed to: Printed in the United States of America
Licensed to: ichapters User An Introduction to Management Science: Quantitative Approaches to Decision Making, Revised Thirteenth Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey
More informationHomework 1 Fall 2000 ENM3 82.1
Homework 1 Fall 2000 ENM3 82.1 Jensen and Bard, Chap. 2. Problems: 11, 14, and 15. Use the Math Programming add-in and the LP/IP Solver for these problems. 11. Solve the chemical processing example in
More informationModeling Linear Programming Problem Using Microsoft Excel Solver
Modeling Linear Programming Problem Using Microsoft Excel Solver ADEKUNLE Simon Ayo* & TAFAMEL Andrew Ehiabhi (Ph.D) Department of Business Administration, Faculty of Management Sciences, University of
More informationChapter 3 Quantitative Demand Analysis
Chapter 3 Quantitative Demand Analysis EX1: Suppose a 10 percent price decrease causes consumers to increase their purchases by 30%. What s the price elasticity? EX2: Suppose the 10 percent decrease in
More informationIndustries that use linear programming models include transportation, energy, telecommunications, and manufacturing.
Linear programming arose as a mathematical model developed during the second world war to plan expenditures and returns in order to reduce costs to the army and increase losses to the enemy. It was kept
More informationThe use of a fuzzy logic-based system in cost-volume-profit analysis under uncertainty
Available online at www.sciencedirect.com Expert Systems with Applications Expert Systems with Applications 36 (2009) 1155 1163 www.elsevier.com/locate/eswa The use of a fuzzy logic-based system in cost-volume-profit
More informationSupply Chain MICROSOFT BUSINESS SOLUTIONS DEMAND PLANNER
Supply Chain MICROSOFT BUSINESS SOLUTIONS DEMAND PLANNER DEMAND PLANNING FOR BUSINESSES Demand planning is the first step towards business planning. As businesses are moving towards a demand-centric environment
More informationISE480 Sequencing and Scheduling
ISE480 Sequencing and Scheduling INTRODUCTION ISE480 Sequencing and Scheduling 2012 2013 Spring term What is Scheduling About? Planning (deciding what to do) and scheduling (setting an order and time for
More informationMEET Project: Management E-learning Experience for Training secondary school's students. Code: LLP-LDV-TOI-10-IT-560
MEET Project: Management E-learning Experience for Training secondary school's students Code: LLP-LDV-TOI-10-IT-560 Lifelong Learning Programme (2007-2013) Leonardo da Vinci Programme Multilateral projects
More informationWhy Learn Statistics?
Why Learn Statistics? So you are able to make better sense of the ubiquitous use of numbers: Business memos Business research Technical reports Technical journals Newspaper articles Magazine articles Basic
More informationOPTIMIZING DEMAND FULFILLMENT FROM TEST BINS. Brittany M. Bogle Scott J. Mason
Proceedings of the 2009 Winter Simulation Conference M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin and R. G. Ingalls, eds. OPTIMIZING DEMAND FULFILLMENT FROM TEST BINS Brittany M. Bogle Scott J.
More informationUse an Excel spreadsheet to solve optimization problems
Math 19 Project 4 (Work in groups of two to four.) Linear Programming Names Use an Excel spreadsheet to solve optimization problems Example 1: The Solar Technology Company manufactures three different
More informationSUPPLY CHAIN PLANNING WITH ADVANCED PLANNING SYSTEMS
SUPPLY CHAIN PLANNING WITH ADVANCED PLANNING SYSTEMS Horst Tempelmeier University of Cologne Department of Production Management Tel. +49 221 470 3378 tempelmeier@wiso.uni-koeln.de Abstract: In the last
More informationManaging risks in a multi-tier supply chain
Managing risks in a multi-tier supply chain Yash Daultani (yash.daultani@gmail.com), Sushil Kumar, and Omkarprasad S. Vaidya Operations Management Group, Indian Institute of Management, Lucknow-226013,
More informationImperfect Competition
Imperfect Competition 6.1 There are only two firms producing a particular product. The demand for the product is given by the relation p = 24 Q, where p denotes the price (in dollars per unit) and Q denotes
More informationOperations and Supply Chain Simulation with AnyLogic
Operations and Supply Chain Simulation with AnyLogic Decision-oriented introductory notes for management students in bachelor and master programs Prof. Dr. Dmitry Ivanov Berlin School of Economics and
More informationCapital Harness. The de facto software solution for the electrical wire harness industry
Capital Harness The de facto software solution for the electrical wire harness industry CAPITAL HARNESS A comprehensive set of software tools that enable the design, engineering for manufacture, validation
More informationA Decision Support System for Performance Evaluation
A Decision Support System for Performance Evaluation Ramadan AbdelHamid ZeinEldin Associate Professor Operations Research Department Institute of Statistical Studies and Research Cairo University ABSTRACT
More informationPRODUCT-MIX ANALYSIS WITH DISCRETE EVENT SIMULATION. Raid Al-Aomar. Classic Advanced Development Systems, Inc. Troy, MI 48083, U.S.A.
Proceedings of the 2000 Winter Simulation Conference J. A. Joines, R. R. Barton, K. Kang, and P. A. Fishwick, eds. PRODUCT-MIX ANALYSIS WITH DISCRETE EVENT SIMULATION Raid Al-Aomar Classic Advanced Development
More informationDIS 300. Quantitative Analysis in Operations Management. Instructions for DIS 300-Transportation
Instructions for -Transportation 1. Set up the column and row headings for the transportation table: Before we can use Excel Solver to find a solution to C&A s location decision problem, we need to set
More informationWestinghouse Waste Simulation and Optimization Software Tool 13493
Westinghouse Waste Simulation and Optimization Software Tool 13493 Kim Mennicken* and Dr. Jörg Aign** *Westinghouse Electric Germany GmbH, Global Waste Management, Dudenstraße 44, D- 68167 Mannheim, Germany,
More informationOracle Value Chain Planning
Oracle Value Chain Planning Integration globaler Supply Chain- Prozesse in heterogenen ERP- Landschaften Henrik Sobolewski PROMATIS AG, Switzerland Hamburg, 20. Juni 2017 Agenda Generic Considerations
More informationTotal Optimal Performance Scores: A Practical Guide for Integrating Financial and Nonfinancial Measures in Performance Evaluation
Total Optimal Performance Scores: A Practical Guide for Integrating Financial and Nonfinancial Measures in Performance Evaluation B Y J OHN B RIGGS, PH.D., CMA; M. CATHY C LAIBORNE, PH.D., CMA, CPA; AND
More informationAggregate Planning and S&OP
Aggregate Planning and S&OP 13 OUTLINE Global Company Profile: Frito-Lay The Planning Process Sales and Operations Planning The Nature of Aggregate Planning Aggregate Planning Strategies 1 OUTLINE - CONTINUED
More informationOperations Research Models and Methods Paul A. Jensen and Jonathan F. Bard. Inventory Level. Figure 4. The inventory pattern eliminating uncertainty.
Operations Research Models and Methods Paul A. Jensen and Jonathan F. Bard Inventory Theory.S2 The Deterministic Model An abstraction to the chaotic behavior of Fig. 2 is to assume that items are withdrawn
More informationSystem Engineering. Instructor: Dr. Jerry Gao
System Engineering Instructor: Dr. Jerry Gao System Engineering - System Engineering Hierarchy - System Modeling - Information Engineering: An Overview - Product Engineering: An Overview - Information
More information2007 Thomson South-Western
Elasticity... allows us to analyze supply and demand with greater precision. is a measure of how much buyers and sellers respond to changes in market conditions THE ELASTICITY OF DEMAND The price elasticity
More informationInventory Control Models
Chapter 12 Inventory Control Models Learning Objectives After completing this chapter, students will be able to: 1. Understand the importance of inventory control. 2. Use inventory control models to determine
More information^ Springer. The Logic of Logistics. Theory, Algorithms, and Applications. for Logistics Management. David Simchi-Levi Xin Chen Julien Bramel
David Simchi-Levi Xin Chen Julien Bramel The Logic of Logistics Theory, Algorithms, and Applications for Logistics Management Third Edition ^ Springer Contents 1 Introduction 1 1.1 What Is Logistics Management?
More informationCHAPTER. Activity Cost Behavior
3-1 CHAPTER Activity Cost Behavior 3-2 Objectives 1. Define cost behavior After for fixed, variable, and studying this mixed costs. chapter, you should 2. Explain the role of be the resource usage model
More informationDECISION-MAKING FOR STRATEGIC SPARE PARTS PRICING LEVELS: AN EVALUATION OF CONSUMER PRODUCTS SUSTAINABILITY
University of Rhode Island DigitalCommons@URI Open Access Dissertations 2014 DECISION-MAKING FOR STRATEGIC SPARE PARTS PRICING LEVELS: AN EVALUATION OF CONSUMER PRODUCTS SUSTAINABILITY Masoud Vaziri University
More informationCh.7 Buying and Supply Strategy.
Module 3 : Value Enhancement Strategies. Ch.7 Buying and Supply Strategy. Edited by Dr. Seung Hyun Lee (Ph.D., CPM) IEMS Research Center, E-mail : lkangsan@iems.co.kr Buying Strategies with Forecasts.
More informationSage 100 ERP 2015 Intelligence Reporting Standard reports
Standard reports Get six ready-to-use reports that give you immediate insight into and across your business. Delivered in the familiar environment of Microsoft Excel, the reports are fully customizable
More informationMGSC 1205 Quantitative Methods I
MGSC 1205 Quantitative Methods I Class Seven Sensitivity Analysis Ammar Sarhan 1 How can we handle changes? We have solved LP problems under deterministic assumptions. find an optimum solution given certain
More informationPowrSym4. A Presentation by. Operation Simulation Associates, Inc. February, 2012
PowrSym4 A Presentation by Operation Simulation Associates, Inc. February, 2012 1 Presentation Contents History of PowrSym Introduction to OSA The PowrSym3 Model PowrSym4 Enhancements 2 PowrSym Background
More informationOPERATING SYSTEMS. Systems and Models. CS 3502 Spring Chapter 03
OPERATING SYSTEMS CS 3502 Spring 2018 Systems and Models Chapter 03 Systems and Models A system is the part of the real world under study. It is composed of a set of entities interacting among themselves
More informationINFORMS Transactions on Education
This article was downloaded by: [37.44.26.3] On: 3 December 217, At: 8:1 Publisher: Institute for Operations Research and the Management Sciences (INFORMS) INFORMS is located in Maryland, USA INFORMS Transactions
More informationSAP Integrated Business Planning (IBP) Towards Digital Now
SAP Integrated Business Planning (IBP) Towards Digital Now Digital transformation is changing the way we sell, buy, distribute, store, plan, communicate, organize, collaborate and generally speak the essence
More informationBalancing Risk and Economics for Chemical Supply Chain Optimization under Uncertainty
Balancing Risk and Economics for Chemical Supply Chain Optimization under Uncertainty Fengqi You and Ignacio E. Grossmann Dept. of Chemical Engineering, Carnegie Mellon University John M. Wassick The Dow
More informationHector Guerrero. Excel Data Analysis. Modeling and Simulation. < J Springer
Hector Guerrero Excel Data Analysis Modeling and Simulation < J Springer Introduction to Spreadsheet Modeling 1 1.1 Introduction 1 1.2 What's an MBA to do?... 2 1.3 Why Model Problems? 3 1.4 Why Model
More informationHomework 1: Basic modeling, analysis and spreadsheet engineering
Homework 1: Basic modeling, analysis and spreadsheet engineering This first assignment is designed to give you a chance to build some relatively simple spreadsheet based models. Use good spreadsheet model
More informationA MANAGER S ROADMAP GUIDE FOR LATERAL TRANS-SHIPMENT IN SUPPLY CHAIN INVENTORY MANAGEMENT
A MANAGER S ROADMAP GUIDE FOR LATERAL TRANS-SHIPMENT IN SUPPLY CHAIN INVENTORY MANAGEMENT By implementing the proposed five decision rules for lateral trans-shipment decision support, professional inventory
More informationChapter 3 Formulation of LP Models
Chapter 3 Formulation of LP Models The problems we have considered in Chapters 1 and 2 have had limited scope and their formulations were very straightforward. However, as the complexity of the problem
More informationCoffee is produced at a constant marginal cost of $1.00 a pound. Due to a shortage of cocoa beans, the marginal cost rises to $2.00 a pound.
Microeconomics, Module 11: Monopoly (Chapter 10) Illustrative Test Questions (The attached PDF file has better formatting.) Updated: June 27, 2005 Question 11.1: Monopoly All but which of the following
More informationJD Edwards World. Forecasting Guide Release A9.3 E
JD Edwards World Forecasting Guide Release A9.3 E20706-02 April 2013 JD Edwards World Forecasting Guide, Release A9.3 E20706-02 Copyright 2013, Oracle and/or its affiliates. All rights reserved. This software
More informationShort-Run Manufacturing Problems at DEC 2. In the fourth quarter of 1989, the corporate demand/supply group of Digital
Short-Run Manufacturing Problems at DEC 2 In the fourth quarter of 1989, the corporate demand/supply group of Digital Equipment Corporation (DEC) was under pressure to come up with a manufacturing plan
More informationMANUFACTURING RESOURCE PLANNING AND ENTERPRISE RESOURCE PLANNING SYSTEMS: AN OVERVIEW
MANUFACTURING RESOURCE PLANNING AND ENTERPRISE RESOURCE PLANNING SYSTEMS: AN OVERVIEW Al-Naimi Assistant Professor Industrial Engineering Branch Department of Production Engineering and Metallurgy University
More informationThe powerful tool for performance management, The GOPPAR Model. a generous container of KPIs for hospitality
economics & information management for hospitality and healthcare The powerful tool for performance management, a generous container of KPIs for hospitality 1 Date : April 2012 Author : Erik Hoogenboom
More informationPerfect Competition and The Supply Curve
chapter: 13 >> Perfect Competition and The Supply Curve The following materials are taken from Chap. 13, Economics, 2 nd ed., Krugman and Wells(2009), Worth Palgrave MaCmillan. 2009 Worth Publishers 1
More informationCHAPTER 3. Quantitative Demand Analysis
CHAPTER 3 Quantitative Demand Analysis Copyright 2014 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education. Chapter Outline
More informationPrinciples of Microeconomics Module 5.1. Understanding Profit
Principles of Microeconomics Module 5.1 Understanding Profit 180 Production Choices of Firms All firms have one goal in mind: MAX PROFITS PROFITS = TOTAL REVENUE TOTAL COST Two ways to reach this goal:
More informationChapter 9: Static Games and Cournot Competition
Chapter 9: Static Games and Cournot Competition Learning Objectives: Students should learn to:. The student will understand the ideas of strategic interdependence and reasoning strategically and be able
More informationMaster of Science in Operations Management University of Arkansas Graduate Course Descriptions and Objectives Last updated: November 7, 2017
1 Master of Science in Operations Management University of Arkansas Graduate Course Descriptions and Objectives Last updated: November 7, 2017 OMGT 5003 Introduction to Operations Management Provides an
More informationDavid Simchi-Levi M.I.T. November 2000
Dynamic Pricing to improve Supply Chain Performance David Simchi-Levi M.I.T. November 2000 Presentation Outline The Direct-to-Consumer Model Motivation Opportunities suggested by DTC Flexible Pricing Strategies
More informationContainer packing problem for stochastic inventory and optimal ordering through integer programming
20th International Congress on Modelling and Simulation, Adelaide, Australia, 1 6 December 2013 www.mssanz.org.au/modsim2013 Container packing problem for stochastic inventory and optimal ordering through
More informationWelcome to: FNSACC507A Provide Management Accounting Information
Welcome to: FNSACC507A Provide Management Accounting Information Week 1 Chapter 1 COST CONCEPTS FNSACC507A Provide Management Accounting Information By the end of this lesson, you will be able to 1. Explain
More informationEconomic Order Quantity
The Definition of EOQ Economic Order Quantity EOQ, or Economic Order Quantity, is defined as the optimal quantity of orders that minimizes total variable costs required to order and hold inventory. The
More informationModel objectives. Main features. Water Evaluation And Planning (WEAP)
Water Evaluation And Planning (WEAP) Model objectives WEAP ( Water Evaluation And Planning system) is a userfriendly software tool that fully integrates water supply, demand, water quality and ecological
More informationFinancial Forecasting:
Financial Forecasting: Tools and Applications Course Description Business and financial forecasting is of extreme importance to managers at practically all levels. It is required for top managers to make
More informationThe asset optimization challenge: Retail design, layout & merchandising.
page 1 The asset optimization challenge: Retail design, layout & merchandising. Reach the optimal balance. a West Monroe Partners white paper by Nathalie Brunet page 2 This article initially appeared in
More informationTotal revenue Quantity. Price Quantity Quantity
s in Competitive Markets WHAT IS A COMPETITIVE MARKET? A perfectly competitive market has the following characteristics: There are many buyers and sellers in the market. The goods offered by the various
More information1) Operating costs, such as fuel and labour. 2) Maintenance costs, such as overhaul of engines and spraying.
NUMBER ONE QUESTIONS Boni Wahome, a financial analyst at Green City Bus Company Ltd. is examining the behavior of the company s monthly transportation costs for budgeting purposes. The transportation costs
More informationOf Finite Stage Markov Decision Process In Policy Determination For Employees Motivation
0 Application 8 МЕЖДУНАРОДНА КОНФЕРЕНЦИЯ 8 INTERNATIONAL CONFERENCE АВАНГАРДНИ МАШИНОСТРОИТЕЛНИ ОБРАБОТКИ ADVANCED MANUFACTURING OPERATIONS Of Finite Stage Markov Decision Process In Policy Determination
More informationOptimization under Uncertainty. with Applications
with Applications Professor Alexei A. Gaivoronski Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Alexei.Gaivoronski@iot.ntnu.no 1 Lecture 2
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Exam Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Economists usually assume that is a fixed input in the run. 1) ) labor; short ) capital;
More informationF u = t n+1, t f = 1994, 2005
Forecasting an Electric Utility's Emissions Using SAS/AF and SAS/STAT Software: A Linear Analysis Md. Azharul Islam, The Ohio State University, Columbus, Ohio. David Wang, The Public Utilities Commission
More informationLinear Cost, Revenue, Profit, Supply, and Demand
Linear Cost, Revenue, Profit, Supply, and Demand Complete the following questions to investigate different types of linear models. Record your responses on this worksheet and the answer sheet. Turn in
More informationReal-time and Intraday Optimization of Multiple Power Generation Units
, ID T6S4P3 Real-time and Intraday Optimization of Multiple Power Generation Units Dr. Rüdiger Franke Hansjürgen Schönung Marcel Blaumann Dr. Alexander Frick Stephan Kautsch ABB AG, Germany 1 INTRODUCTION...
More informationEnterpriseOne JDE5 Forecasting PeopleBook
EnterpriseOne JDE5 Forecasting PeopleBook May 2002 EnterpriseOne JDE5 Forecasting PeopleBook SKU JDE5EFC0502 Copyright 2003 PeopleSoft, Inc. All rights reserved. All material contained in this documentation
More informationPHD. THESIS -ABSTRACT-
Investeşte în oameni! Proiect cofinantat din Fondul Social European prin Programul Operaţional Sectorial pentru Dezvoltarea Resurselor Umane 2007 2013 Eng. Lavinia-Gabriela SOCACIU PHD. THESIS -ABSTRACT-
More informationUNIT-II Enterprise Resource Planning
UNIT-II Enterprise Resource Planning 1 Syllabus Evolution of ERP- MRP and MRP II, Structure Of ERP- Two Tier Architecture, Three Tier Architecture, Electronic Data Processing, Management Information System,
More informationMath 1314 Lesson 8 Business Applications: Break Even Analysis, Equilibrium Quantity/Price
Math 1314 Lesson 8 Business Applications: Break Even Analysis, Equilibrium Quantity/Price Three functions of importance in business are cost functions, revenue functions and profit functions. Cost functions
More informationSimulation-Based Analysis and Optimisation of Planning Policies over the Product Life Cycle within the Entire Supply Chain
From the SelectedWorks of Liana Napalkova June, 2009 Simulation-Based Analysis and Optimisation of Planning Policies over the Product Life Cycle within the Entire Supply Chain Galina Merkuryeva Liana Napalkova
More informationLinear Programming for Revenue Management in Hotel Industry
Linear Programming for Revenue Management in Hotel Industry Mrs Shreelatha Rao, MSc, MBA, PGDHE Welcomgroup Graduate School of Hotel Administration Manipal University Manipal 576 104 Karnataka - India
More informationPower-to-Gas: Real-time Optimization
Power-to-Gas: Real-time Optimization Laurence Grand-Clément Sezin Afşar PersEE Innovation SESO 2017, May 31st Laurence Grand-Clément, Sezin Afşar Power-to-Gas: Real-time Optimization 1/17 Outline Introduction
More informationAdvanced Supply Chain Management (POM 625) - Lecture 1 - Dr. Jinwook Lee
Advanced Supply Chain Management (POM 625) - Lecture 1 - Dr. Jinwook Lee Topics of Lecture 1 - Introduction - What is Supply Chain Management? - Issues of SCM - Goals, importance, and strategies of SCM
More informationTest Bank Business Intelligence and Analytics Systems for Decision Support 10th Edition Sharda
Test Bank Business Intelligence and Analytics Systems for Decision Support 10th Edition Sharda Instant download and all Business Intelligence and Analytics Systems for Decision Support 10th Edition Sharda
More informationVendor Managed Inventory vs. Order Based Fulfillment in a. Specialty Chemical Company
Vendor Managed Inventory vs. Order Based Fulfillment in a Specialty Chemical Company Introduction By Dimitrios Andritsos and Anthony Craig Bulk chemicals manufacturers are considering the implementation
More informationApplication of the method of data reconciliation for minimizing uncertainty of the weight function in the multicriteria optimization model
archives of thermodynamics Vol. 36(2015), No. 1, 83 92 DOI: 10.1515/aoter-2015-0006 Application of the method of data reconciliation for minimizing uncertainty of the weight function in the multicriteria
More informationAn Inventory Model with Demand Dependent Replenishment Rate for Damageable Item and Shortage
Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7 9, 2014 An Inventory Model with Demand Dependent Replenishment Rate for Damageable
More informationSupply Chain Inventory Policy Analyser (SCIPA) Software Package -User Manual
Supply Chain Inventory Policy Analyser (SCIPA) Software Package -User Manual Department of Mechanical Engineering National Institute of Technology Calicut The document giving details about how to use the
More informationPRODUCTION PLANNING MODULE
Anar Pharmaceuticals Limited ERP Project In Sales & Distribution Module I had recommended: PRODUCTION PLANNING MODULE 1. Monthly Corporate Sales Budget Process (Refer Sales Budget - page 32) & 2. Macro
More informationInventory models for deteriorating items with discounted selling price and stock dependent demand
Inventory models for deteriorating items with discounted selling price and stock demand Freddy Andrés Pérez ( fa.perez10@uniandes.edu.co) Universidad de los Andes, Departamento de Ingeniería Industrial
More information. This function gives the supplier s behavior with respect to price and quantity.
Demand and supply functions are used to describe the consumer and manufacturer behavior with respect to the price of a product or service and the quantity of a product or service. Different textbooks may
More informationLecture : Applications of Maxima and Minima (Optimization) MTH 124
The motivation to minimize or maximize a function is strictly determined by the context of the problem. For example we may want to maximize the area of a fenced in area given a fixed amount of fencing
More information