Nonstandard Problmes Produced by E. Gretchen Gascon.

Slides:



Advertisements
Similar presentations
Chapter 5: Linear Programming: The Simplex Method
Advertisements

Minimize Problems Produced by E. Gretchen Gascon.
Simplex Method Example 4.2 # 17 Produced by E. Gretchen Gascon.
Operation Research Chapter 3 Simplex Method.
L17 LP part3 Homework Review Multiple Solutions Degeneracy Unbounded problems Summary 1.
LECTURE 14 Minimization Two Phase method by Dr. Arshad zaheer
Transportation Problem (TP) and Assignment Problem (AP)
Chapter 6 Linear Programming: The Simplex Method
Dr. Sana’a Wafa Al-Sayegh
Copyright (c) 2003 Brooks/Cole, a division of Thomson Learning, Inc
L16 LP part2 Homework Review N design variables, m equations Summary 1.
Sections 4.1 and 4.2 The Simplex Method: Solving Maximization and Minimization Problems.
1. The Simplex Method for Problems in Standard Form 1.
Chapter 6 Linear Programming: The Simplex Method Section 3 The Dual Problem: Minimization with Problem Constraints of the Form ≥
Chapter 6 Linear Programming: The Simplex Method
Linear Inequalities and Linear Programming Chapter 5
Chapter 7 LINEAR PROGRAMMING.
The Simplex Method: Standard Maximization Problems
5.4 Simplex method: maximization with problem constraints of the form
The Simplex Algorithm An Algorithm for solving Linear Programming Problems.
Operation Research Chapter 3 Simplex Method.
1 Linear programming simplex method This presentation will help you to solve linear programming problems using the Simplex tableau.
Solving Systems of Linear Equations Part Pivot a Matrix 2. Gaussian Elimination Method 3. Infinitely Many Solutions 4. Inconsistent System 5. Geometric.
Finite Mathematics & Its Applications, 10/e by Goldstein/Schneider/SiegelCopyright © 2010 Pearson Education, Inc. 1 of 99 Chapter 4 The Simplex Method.
5.6 Maximization and Minimization with Mixed Problem Constraints
Chapter 4 The Simplex Method
Stevenson and Ozgur First Edition Introduction to Management Science with Spreadsheets McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies,
LINEAR PROGRAMMING SIMPLEX METHOD.
Learning Objectives for Section 6.2
Chapter 6 Linear Programming: The Simplex Method
EE/Econ 458 The Simplex Method using the Tableau Method
Simplex Algorithm.Big M Method
Chapter 6 Linear Programming: The Simplex Method Section 2 The Simplex Method: Maximization with Problem Constraints of the Form ≤
ECE 556 Linear Programming Ting-Yuan Wang Electrical and Computer Engineering University of Wisconsin-Madison March
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Learning Objectives for Section 6.4 The student will be able to set up and solve linear programming problems.
1 1 Slide © 2000 South-Western College Publishing/ITP Slides Prepared by JOHN LOUCKS.
Kerimcan OzcanMNGT 379 Operations Research1 Linear Programming: The Simplex Method Chapter 5.
1 1 © 2003 Thomson  /South-Western Slide Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Setting Up the Initial Simplex Tableau and Finding the Pivot Element Example 4.2 # 17 Produced by E. Gretchen Gascon.
1 1 © 2003 Thomson  /South-Western Slide Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Public Policy Modeling Simplex Method Tuesday, October 13, 2015 Hun Myoung Park, Ph.D. Public Management & Policy Analysis Program Graduate School of International.
Chapter 6 Linear Programming: The Simplex Method Section R Review.
4  The Simplex Method: Standard Maximization Problems  The Simplex Method: Standard Minimization Problems  The Simplex Method: Nonstandard Problems.
Chapter 6 Linear Programming: The Simplex Method Section 3 The Dual Problem: Minimization with Problem Constraints of the Form ≥
1 1 Slide © 2005 Thomson/South-Western Linear Programming: The Simplex Method n An Overview of the Simplex Method n Standard Form n Tableau Form n Setting.
Chapter 4 Linear Programming: The Simplex Method
Chapter 6 Linear Programming: The Simplex Method Section 4 Maximization and Minimization with Problem Constraints.
THE SIMPLEX ALGORITHM Step 1 The objective row is scanned and the column containing the most negative term is selected (pivotal column) - indicate with.
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Learning Objectives for Section 6.3 The student will be able to formulate the dual problem. The student.
Linear Inequalities and Linear Programming Chapter 5 Dr.Hayk Melikyan/ Department of Mathematics and CS/ 5.5 Dual problem: minimization.
Simplex Method Simplex: a linear-programming algorithm that can solve problems having more than two decision variables. The simplex technique involves.
Copyright © 2006 Brooks/Cole, a division of Thomson Learning, Inc. Linear Programming: An Algebraic Approach 4 The Simplex Method with Standard Maximization.
Decision Support Systems INF421 & IS Simplex: a linear-programming algorithm that can solve problems having more than two decision variables.
GOOD MORNING CLASS! In Operation Research Class, WE MEET AGAIN WITH A TOPIC OF :
The Simplex Method. and Maximize Subject to From a geometric viewpoint : CPF solutions (Corner-Point Feasible) : Corner-point infeasible solutions 0.
5.5 Dual problem: minimization with problem constraints of the form Associated with each minimization problem with constraints is a maximization problem.
Simplex Algorithm.Big M Method
LINEAR PROGRAMMING.
Linear programming Simplex method.
Linear Algebra Lecture 4.
Chapter 8: Lesson 8.1 Matrices & Systems of Equations
Chapter 4 Linear Programming: The Simplex Method
Lial/Hungerford/Holcomb/Mullins: Mathematics with Applications 11e Finite Mathematics with Applications 11e Copyright ©2015 Pearson Education, Inc. All.
The Simplex Method: Nonstandard Problems
The Simplex Method The geometric method of solving linear programming problems presented before. The graphical method is useful only for problems involving.
Linear programming Simplex method.
D1 Discrete Mathematics
Copyright © 2019 Pearson Education, Inc.
THE SIMPLEX ALGORITHM Step 1
Presentation transcript:

Nonstandard Problmes Produced by E. Gretchen Gascon

Concept of Mixed Problems Mixed problems are problems which have both greater than and less than constraints. Mixed problems cannot use the DUEL method for solving (Used in Section 4.3) (Do NOT transpose the matrix to convert to maximization problem) Mixed problems cannot use the Excel SOLVER function. See solving Nonstandard Problem steps page 189. Use slack variables + s, for ≤ and use surplus variable –s for ≥ and use +a (artificial variables) for =. Always eliminate the artificial variable first. (find row in which the artificial variable exists and then pivot on the leftmost positive entry in that row that is not in an artificial variable column. Basic variable – is the nonzero variable in a column of otherwise zeros. Investigating quotients – only use consider quotients >= 0

Problem 4.4 # 15 Step 1 – Convert problem to a maximization problem writing the negative of the w equation. Step 2 – Add slack variables and subtract surplus variables as needed.

Problem 4.4 # 15 con’t Step 3 – Write the initial simplex tableau Step 4 – If any basic variable(s1,s2,, z) has a negative value, locate the nonzero number in that variable’s column, and note what row it is in. (Row 2) Step 5- In the row located in step 4, find the positive entry that is farthest to the left, and note what column it is in. (Col 1)

Problem 4.4 # 15 con’t Step 6 – In the column found in Step 5, choose a pivot by investigating quotients. 150/10 and 100/20, 100/20 is smallest ( Row 2 Col 1 is pivot element) Step 7 – Use row operations to change the other number in the pivot column to 0

Problem 4.4 # 15 con’t (Basic variable are now y1, s1, z) (s2 is no longer a basic variable, because the column now has all non-zero elements and none of the basic variables mentioned are negative, you do not have to repeat steps 4 – 5) Step 8 Once a feasible solution has been found, continue to use the simplex method until the optimal solution is found. ( In this case, Column 3 has a negative in the bottom row. Select that as the pivot column and use investigating quotients to choose row 2 col 3 as the pivot element.

Problem 4.4 # 15 con’t Variable are = 0 which have all non zero values in the column Variable which have only one number can be converted into equations Note: The matrix give the value of z but, w is the opposite of z. (note conversion at the beginning of problem.

Review Please post comments, questions, regarding this slide presentation in the Main forum