PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J. 07458 B-1 PENYELESAIAN.

Slides:



Advertisements
Similar presentations
PowerPoint Slides by Robert F. BrookerCopyright (c) 2001 by Harcourt, Inc. All rights reserved. Linear Programming Mathematical Technique for Solving Constrained.
Advertisements

© 2003 Anita Lee-Post Linear Programming Part 2 By Anita Lee-Post.
Planning with Linear Programming
Linear Programming Problem
Linear Programming (LP) Decision Variables Objective (MIN or MAX) Constraints Graphical Solution.
Chapter 2: Modeling with Linear Programming & sensitivity analysis
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 9-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 9 Linear.
2-1 Linear Programming: Model Formulation and Graphical Solution Chapter 2 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
LINEAR PROGRAMMING (LP)
8/27: Linear Programming Lecture: LP Small Groups Homework.
Managerial Decision Modeling with Spreadsheets
© 2008 Prentice-Hall, Inc. Chapter 7 To accompany Quantitative Analysis for Management, Tenth Edition, by Render, Stair, and Hanna Power Point slides created.
19 Linear Programming CHAPTER
Linear Programming Introduction George B Dantzig developed LP in It is a problem solving approach designed to help managers/decision makers in planning.
B Linear Programming PowerPoint presentation to accompany
© 2006 Prentice Hall, Inc.B – 1 Operations Management Module B – Linear Programming © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany Heizer/Render.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 7-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 7 Linear.
Operations Management
Operations Management
B-1 Operations Management Linear Programming Module B.
1 2TN – Linear Programming  Linear Programming. 2 Linear Programming Discussion  Requirements of a Linear Programming Problem  Formulate:  Determine:Graphical.
1 Lecture 2 & 3 Linear Programming and Transportation Problem.
To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Seventh Edition © 2004 Prentice Hall, Inc. All rights reserved. Linear Programming.
B-1 Operations Management Linear Programming Module B.
Linear Programming: Model Formulation and Graphical Solution
Linear Programming Models: Graphical Methods 5/4/1435 (1-3 pm)noha hussein elkhidir.
FORMULATION AND GRAPHIC METHOD
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. 1.
Linear programming. Linear programming… …is a quantitative management tool to obtain optimal solutions to problems that involve restrictions and limitations.
1© 2003 by Prentice Hall, Inc. Upper Saddle River, NJ The Wyndor Glass Company Problem (Hillier and Liberman) The Wyndor Glass Company is planning.
Chapter 4: Modeling and Analysis
Linear Programming Chapter 13 Supplement.
Module B: Linear Programming
PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-1 Operations.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 6S Linear Programming.
Operations Management
___________________________________________________________________________ Operations Research  Jan Fábry Linear Programming.
B Linear Programming PowerPoint presentation to accompany
1 Additional examples LP Let : X 1, X 2, X 3, ………, X n = decision variables Z = Objective function or linear function Requirement: Maximization of the.
THE GALAXY INDUSTRY PRODUCTION PROBLEM -
___________________________________________________________________________ Quantitative Methods of Management  Jan Fábry Linear Programming.
Transparency Masters to accompany Heizer/Render – Principles of Operations Management, 5e, and Operations Management, 7e © 2004 by Prentice Hall, Inc.,
 A concert promoter wants to book a rock group for a stadium concert. A ticket for admission to the stadium playing field will cost $125, and a ticket.
Linear Programming Introduction: Linear programming(LP) is a mathematical optimization technique. By “Optimization” technique we mean a method which attempts.
1/24: Linear Programming & Sensitivity Analysis Review: –LP Requirements –Graphical solutions Using MS Excel for Linear Programming Sensitivity Analysis.
LP: Summary thus far Requirements Graphical solutions Excel Sensitivity Analysis.
PowerPoint Slides by Robert F. BrookerHarcourt, Inc. items and derived items copyright © 2001 by Harcourt, Inc. Managerial Economics in a Global Economy.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 6S Linear Programming.
To accompany Quantitative Analysis for Management, 7e by Render/ Stair 7-1 © 2000 by Prentice Hall, Inc., Upper Saddle River, N.J Quantitative Analysis.
Saba Bahouth 1 Supplement 6 Linear Programming. Saba Bahouth 2  Scheduling school busses to minimize total distance traveled when carrying students 
PowerPoint presentation to accompany Heizer/Render - Principles of Operations Management, 5e, and Operations Management, 7e © 2004 by Prentice Hall, Inc.,
LINEAR PROGRAMMING.
1 Optimization Techniques Constrained Optimization by Linear Programming updated NTU SY-521-N SMU EMIS 5300/7300 Systems Analysis Methods Dr.
© 2008 Prentice Hall, Inc.B – 1 Operations Management Module B – Linear Programming PowerPoint presentation to accompany Heizer/Render Principles of Operations.
Linear Programming Short-run decision making model –Optimizing technique –Purely mathematical Product prices and input prices fixed Multi-product production.
© 2008 Prentice-Hall, Inc. Linear Programming Models: Graphical and Computer Methods.
Warm-upWarm-up Sketch the region bounded by the system of inequalities: 1) 2) Sketch the region bounded by the system of inequalities: 1) 2)
Linear Programming Graphical Solution. Graphical Solution to an LP Problem This is easiest way to solve a LP problem with two decision variables. If there.
© 2009 Prentice-Hall, Inc. 7 – 1 Decision Science Chapter 3 Linear Programming: Maximization and Minimization.
Linear Programming. George Dantzig 1947 NarendraKarmarkar Pioneers of LP.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 7-1 1© 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 7 Linear.
6s-1Linear Programming William J. Stevenson Operations Management 8 th edition.
Linear Programming Models: Graphical and Computer Methods 7 To accompany Quantitative Analysis for Management, Twelfth Edition, by Render, Stair, Hanna.
Chapter 2 Linear Programming Models: Graphical and Computer Methods
Linear Programming.
Linear Programming Models: Graphical and Computer Methods
Operations Management Linear Programming Module B
Copyright © 2014, 2010, 2007 Pearson Education, Inc.
Module B Linear Programming.
Linear Programming.
Presentation transcript:

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-1 PENYELESAIAN LP  Masalah LP dapat diselesaikan dengan : 1.Metode Grafik 2.Metode Simplek  Masalah LP diilustrasikan dan dipecahkan dengan metode grafik, jika model tersebut hanya memiliki dua variabel keputusan

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-2 Requirements of a Linear Programming Problem 1 Must seek to maximize or minimize some quantity (the objective function) 2 Presence of restrictions or constraints - limits ability to achieve objective 3 Must be alternative courses of action from which to choose 4 Objectives and constraints must be expressible as linear equations or inequalities

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-3 Metode Grafik Langkah penyelesaian : 1.Gambarkan fungsi kendala dalam bentuk persamaan pada sumbu Cartesius 2.Tentukan daerah solusi layak (feasible solution) dengan memperhatikan tanda ketidaksamaan fungsi kendala. 3.Gambarkan fungsi tujuan, geser garis tsb ke lokasi titik solusi yang optimal 4.Selesaikan persamaan-persamaan pada titik solusi untuk menentukan solusi optimal

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-4  Scheduling school busses to minimize total distance traveled when carrying students  Allocating police patrol units to high crime areas in order to minimize response time to 911 calls  Scheduling tellers at banks to that needs are met during each hour of the day while minimizing the total cost of labor Examples of Successful LP Applications

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-5 Examples of Successful LP Applications - continued  Picking blends of raw materials in feed mills to produce finished feed combinations at minimum costs  Selecting the product mix in a factory to make best use of machine- and labor-hours available while maximizing the firm’s profit  Allocating space for a tenant mix in a new shopping mall so as to maximize revenues to the leasing company

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-6 Formulating Linear Programming Problems  Assume:  You wish to produce two products (1) Walkman AM/FM/Cassette and (2) Watch-TV  Walkman takes 4 hours of electronic work and 2 hours assembly  Watch-TV takes 3 hours electronic work and 1 hour assembly  There are 240 hours of electronic work time and 100 hours of assembly time available  Profit on a Walkman is $7; profit on a Watch-TV $5

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-7 Formulating Linear Programming Problems - continued  Let:  X 1 = number of Walkmans  X 2 = number of Watch-TVs  Then:  4X 1 + 3X 2  240electronics constraint  2X 1 + 1X 2  100assembly constraint  7X 1 + 5X 2 = profitmaximize profit

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-8  Draw graph with vertical & horizontal axes (1st quadrant only)  Plot constraints as lines, then as planes  Use ( X 1,0), (0, X 2 ) for line  Find feasible region  Find optimal solution  Corner point method  Iso-profit line method Graphical Solution Method

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-9 Shader Electronic Company Problem Hours Required to Produce 1 Unit DepartmentX1X1 Walkmans X2X2 Watch-TV’s Available Hours This Week Electronic43240 Assembly21100 Profit/unit$7$5 Constraints: 4x 1 + 3x 2  240 (Hours of Electronic Time) 2x 1 + 1x 2  100 (Hours of Assembly Time) Objective:Maximize: 7x 1 + 5x 2

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-10 Shader Electronic Company Constraints Number of Walkmans (X 1 ) Number of Watch-TVs (X 2 ) Electronics (Constraint A) Assembly (Constraint B)

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-11 Shader Electronic Company Feasible Region Number of Walkmans (X 1 ) Number of Watch-TVs (X 2 ) Electronics (Constraint A) Assembly (Constraint B) Feasible Region

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-12 Shader Electronic Company Iso-Profit Lines Number of Walkmans (X 1 ) Number of Watch-TVs (X 2 ) Electronics (Constraint A) Assembly (Constraint B) 7*X 1 + 5*X 2 = 210 7*X 1 + 5*X 2 = 420

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-13 Shader Electronic Company Solution Number of Walkmans (X 1 ) Number of Watch-TVs (X 2 ) Electronics (Constraint A) Assembly (Constraint B) ISO-Profit Line Solution Point (X 1 =30, X 2 =40)

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-14 Shader Electronic Company Solution Corner Point Solution Number of Walkmans (X 1 ) Number of Watch-TVs (X 2 ) Electronics (Constraint A) Assembly (Constraint B) Possible Corner Point Solution Optimal solution

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-15 You’re an analyst for a division of Kodak, which makes BW & color chemicals. At least 30 tons of BW and at least 20 tons of color must be made each month. The total chemicals made must be at least 60 tons. How many tons of each chemical should be made to minimize costs? BW: $2,500 manufacturing cost per month Color: $ 3,000 manufacturing cost per month © 1995 Corel Corp. Minimization Example

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-16  Decision variables  X 1 = tons of BW chemical produced  X 2 = tons of color chemical produced  Objective  Minimize Z = 2500 X X 2  Constraints  X 1  30 (BW); X 2  20 (Color)  X 1 + X 2  60 (Total tonnage)  X 1  0; X 2  0 (Non-negativity) Formulation of Solution

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-17 Graphical Solution FeasibleRegion Tons, Color Chemical (X 2 ) Tons, BW Chemical (X 1 ) BW Color Total Find values for X 1 + X 2  60. X 1  30, X 2  20.

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-18 FeasibleRegion Tons, Color Chemical Tons, BW Chemical BW Color Total Find corner points. A B Optimal Solution: Corner Point Method

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J B-19 Sensitivity Analysis  Projects how much a solution might change if there were changes in variables or input data.  Shadow price (dual) - value of one additional unit of a resource