Linear Optimization using Excel

Slides:



Advertisements
Similar presentations
WEEK-2 LINEAR PROGRAMMING Waheed Ullah PhD Scholar INU.
Advertisements

1Introduction to Linear ProgrammingLesson 2 Introduction to Linear Programming.
LINEAR PROGRAMMING (LP)
Introduction to Mathematical Programming
Linear Programming. Introduction: Linear Programming deals with the optimization (max. or min.) of a function of variables, known as ‘objective function’,
Solving Linear Programming Models. Topics Computer Solution Sensitivity Analysis.
OPSM 301 Operations Management
Linear Programming.
Planning with Linear Programming
Linear Programming Problem
___________________________________________________________________________ Operations Research  Jan Fábry Applications Linear Programming.
B-1 Operations Management Linear Programming Module B - New Formulations.
Marketing Applications: Media selection
Chapter 2 Linear Programming Models: Graphical and Computer Methods © 2007 Pearson Education.
Managerial Economics and Organizational Architecture, 5e Chapter 17: Divisional Performance Evaluation McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill.
Example 3 Financial Model Rate of Return Summation Variable/Constraint
1 Ardavan Asef-Vaziri Nov-2010Theory of Constraints 1- Basics Practice; Follow the 5 Steps Process Purchased Part $5 / unit RM1 $20 per unit RM2 $20 per.
Linear Programming Introduction. linear function linear constraintsA Linear Programming model seeks to maximize or minimize a linear function, subject.
Linear and Integer Programming Models
Lecture outline Support vector machines. Support Vector Machines Find a linear hyperplane (decision boundary) that will separate the data.
B-1 Operations Management Linear Programming Module B - Harder Formulations.
1 Ardavan Asef-Vaziri Nov-2010Theory of Constraints 1- Basics Purchased Part $5 / unit RM1 $20 per unit RM2 $20 per unit RM3 $25 per unit $90 / unit 110.
Previously in IEMS 310… Notation of optimization problems Linear Programs Sensitivity Analysis Duality Piecewise linear functions Assignment Problems.
Linear Programming Example 2 Alternate Optimal Solutions.
Solver Linear Problem Solving MAN Micro-computers & Their Applications.
STRATEGIC MANAGEMENT ACCOUNTING Anushka De Silva.
Linear Programming Sensitivity of the Objective Function Coefficients.
4-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Linear Programming: Modeling Examples Chapter 4.
Product Mix Problem Monet company makes four types of frames.
Module B: Linear Programming
Do the algebra required to find a simultaneous solutions to these two equations (from last class): 3x 1 + x 2  3 x 1 + 3x 2  5 1.
CDAE Class 11 Oct. 3 Last class: Result of Quiz 2 2. Review of economic and business concepts Today: Result of Quiz 2 3. Linear programming and applications.
BUSINESS MATHEMATICS & STATISTICS. LECTURE 45 Planning Production Levels: Linear Programming.
CDAE Class 12 Oct. 5 Last class: Quiz 3 3. Linear programming and applications Today: Result of Quiz 3 3. Linear programming and applications Next.
Linear Programming with Excel Solver.  Use Excel’s Solver as a tool to assist the decision maker in identifying the optimal solution for a business decision.
In the Name Of Allah DSS Lab 04 Solving Problems 1Tahani ALdweesh.
LINEAR PROGRAMMING APPLICATIONS IN MARKETING, FINANCE, AND OPERATIONS MANAGEMENT (2/3) Chapter 4 MANGT 521 (B): Quantitative Management.
1 A Linear Programming model seeks to maximize or minimize a linear function, subject to a set of linear constraints. The linear model consists of the.
4-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Linear Programming: Modeling Examples Chapter 4- Part2.
4-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Linear Programming: Modeling Examples Chapter 4.
Math Programming Concept of Optimization (L.O. a ) Linear Programming Managerial Value of Information (L.O. d) Theory (L.O. b) Example Applications (L.O.
Linear Programming –Strategic Allocation of Resources Decision Making with Excel Simulation 1.
CDAE Class 12 Oct. 4 Last class: 2. Review of economic and business concepts Today: 3. Linear programming and applications Quiz 3 (sections 2.5 and.
LINEAR PROGRAMMING.
OPSM 301 Operations Management Class 11: Linear Programming using Excel Koç University Zeynep Aksin
LINEAR PROGRAMMING 3.4 Learning goals represent constraints by equations or inequalities, and by systems of equations and/or inequalities, and interpret.
Asset Allocation What is it and how can you benefit? Insurance Concepts.
Adeyl Khan, Faculty, BBA, NSU 1 Introduction to Linear Programming  A Linear Programming model seeks to maximize or minimize a linear function, subject.
Linear Programming Wyndor Glass Co. 3 plants 2 new products –Product 1: glass door with aluminum framing –Product 2: 4x6 foot wood frame window.
Don Sutton Spring LP Basic Properties Objective Function – maximize/minimize profit/cost Resource Constraints – labor, money Decision.
March 16, 2016A&MIS 5251 Session 28 A&MIS 525 May 8, 2002 William F. Bentz.
EMGT 5412 Operations Management Science Nonlinear Programming: Introduction Dincer Konur Engineering Management and Systems Engineering 1.
Chapter 6 Integer, Goal, and Nonlinear Programming Models © 2007 Pearson Education.
1 Linear Programming 2 A Linear Programming model seeks to maximize or minimize a linear function, subject to a set of linear constraints. The linear.
Appendix A with Woodruff Edits Linear Programming Using the Excel Solver Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin.
Class 10: Introduction to Linear Programming
Chapter 2 Linear Programming Models: Graphical and Computer Methods
Baldwin Bicycle Company
Introduction to Linear Programs
Unit 5 Portfolio Management
CHAPTER 6 RISK The Concept of Variability E(R) = Sum of (oi x pi ),
Linear Programming Wyndor Glass Co. 3 plants 2 new products
Model 3: A Linear Model By Evan Nixon.
Model 7: Results and Sensitivity Analysis
Linear Programming Introduction.
Optimization Theory Linear Programming
Optimization Models Module 9.
Chapter 7.
Linear Programming Introduction.
Introduction to Portfolio Management
Presentation transcript:

Linear Optimization using Excel

3-Steps Optimization Process Model Development Optimization Evaluation Model development is the most difficult part of the optimization process. The evaluation involves sensitivity analysis of the optimized solution. It consists of the sensitivity analysis of the variables and the constraints.

Common Features Objective Input Variables Decision variables Constraints Objective to maximize or minimize Input variables may be resources and profits How many to make or allocate Constraints might be machine hours, labour hours or demand.

Case 1 Saleem & Co manufactures jugs and glasses using machines A and B. The following hours are required to make one jug and glass: Machine A: 2 hours (for jug) and 1.5 hours (for glass) Machine B: 1.4 hours (for jug) and 1.1 hours (for glass) Total 400 hours are available on Machine A and 350 hours on Machine B. Contribution margin from jug is Rs. 15 and from glass Rs. 10. Required: Determine the optimal mix of jugs and glasses in order to maximize the contribution

Case 2 Pak-Suzuki makes two types of air-filters: regular and premium. The unit profit of each of them is Rs. 500 and Rs. 700. Both uses the following inputs: Labour Hours: 3 (Reg.) and 4 (Prem.) ---- Max. Cap. 3000 hrs Plastic components: 2 (Reg.) and 3 (Prem.) --- Max. Cap. 2500 comp. Machine hours: 0.75 (Reg.) and 1.20 (Prem.) --- Max. Cap. 5000 hrs Required: Optimal product mix of the regular and the premium air filters

Case 3 Pak-Suzuki makes two types of air-filters: regular and premium. The unit profit of each of them is Rs. 500 and Rs. 700. Both uses the following inputs: Labour Hours: 3 (Reg.) and 4 (Prem.) ---- Max. Cap. 3000 hrs Plastic components: 2 (Reg.) and 3 (Prem.) --- Max. Cap. 2500 comp. Machine hours: 0.75 (Reg.) and 1.20 (Prem.) --- Max. Cap. 5000 hrs Demand: Max. (Reg.) 500 and Max. (Prem.) 400 Required: Optimal product mix of the regular and the premium air filters

Case 4 Required: Use the following information to find the optimal product mix of mice, keyboards and USB hubs.

Case 5 Investment Optimization Ali wants to invest Rs. 1,000,000/- in the financial assets in Pakistan. His analysis shows the following expected profits on the major asset classes: Derivatives 28% High Risk Equity 21% High Risk Bonds 16% Low Risk Money Market 13% Low Risk He does not want to invest more than 35% in anyone of the asset classes and more than 60% in the high risk assets. Required: Optimal portfolio mix that maximizes the annual return.