1 / 10

Operations Research 1 Dr. El-Sayed Badr

Operations Research 1 Dr. El-Sayed Badr Associate Professor of Computers & Informatics - Benha University Alsayed.badr@fsc.bu.edu.eg. Dr. El-Sayed Badr 2014. Terminology. A solution is any specification of values for the decision variables.

jsingh
Download Presentation

Operations Research 1 Dr. El-Sayed Badr

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Operations Research 1 Dr. El-Sayed Badr Associate Professor of Computers & Informatics - Benha University Alsayed.badr@fsc.bu.edu.eg Dr. El-Sayed Badr 2014

  2. Terminology A solution is any specification of values for the decision variables. A feasible Solution is a solution for which all the constraints are satisfied. The feasible region is the set of all feasible solutions. An Optimal Solution is a feasible solution that has the most favorable value of the objective function. A Corner-Point Solutioncorresponds to a solution of the subset of equations corresponding to the constraints meeting at that corner point (vertex) A Corner-point feasible (CPF) solution is a solution that lies at a corner of the feasible region . A Basic Solution is a corner-point solution A Basic Feasible Solution is a CPF solution for which all the variables are greater than or equal to zero.

  3. Conceptual Outline of the Steps of the Simplex Algorithm Step 0: Using the standard form determine a starting basic feasible solution by setting n-m non-basic variables to zero. Step 1: Select an entering variable from among the current non-basic variables, which gives the largest per-unit improvement in the value of the objective function. If none exists stop; the current basic solution is optimal. Otherwise go to Step 2. Step 2: Select a leaving variable from among the current basic variables that must now be set to zero (become non-basic) when the entering variable becomes basic. Step 3: Determine the new basic solution by making the entering variable, basic; and the leaving variable, non-basic, and return to Step 1.

  4. Simplex Algorithm 4

  5. Klee-Minty Question1: Solve the following Linear Problem 5

  6. Klee - Minty 6

  7. Klee - Minty 7

  8. Klee - Minty 8

  9. Klee - Minty 9

  10. Simplex Algorithm Question2: What is the situationif our problem Contains constraints of the kind ( <= , >= and = = ) ? Answer2: 1- Dual Simplex Algorithm. 2- Two-Phase Method. 3- Big M-Method. 4-……. 10

More Related