KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS

Department of Mathematical

SYLLABUS (101) (Semester I, 2001-2002)

(Dr. Suliman Al-Homidan)

Course # Math 480
Title Linear and Nonlinear Programming

Prerequisite Math 280, ICS 101 or ICS 102

Textbook Linear and Nonlinear Programming by E.G. Luenberger, 2nd edition (1994).

Objectives

The course deals with the basic ideas of mathematical programming (linear and nonlinear). We shall see how simple mathematics plays a significant role in the development of these ideas. The students will be asked to work out the computational implementation of a numerical algorithm for solving Linear and Nonlinear Programming problems and do presentations.

Current Catalogue Description

Formulation of linear programs. Basic properties of linear programs. The simplex method. Duality. Necessary and sufficient conditions for unconstrained problems. Minimization of convex functions. A method of solving unconstrained problems. Equality and inequahit)’ constrained optimization. The Lagrange multipliers. The Kuhn-Tucker conditions. A method of solving constrained problems.

Week #

Sections

Topics

1

2.1-2.3

Introduction, Examples of Linear Programming Problems, Basic Solutions

2

2.4-2.5

The Fundamental Theorem of Linear Programming, Relations to Convexity

3

3.1-3.5

Pivots, Adjacent Extreme Points, Determining a Minimum Feasible Solution, Computational Procedure~Simplex Method, Artificial Variables

4

3.7-3.8

Matrix Form of the Simplex Method, The Revised Simplex Method

5

4.1-4.2

Dual Linear Programs, The Duality Theorem

6

4.3-4.5

Relations to the Simplex Procedure, Sensitivity and Complementary Slackness, The Dual Simplex Method

7

5.1-5.4

Transportation Problem

8

6.1-6.4

First Order Necessary Conditions, Examples of Unconstarined Problems, Second-Order Conditions, Convex and Concave Functions,

9

6.5, 7.6, 7.8

Minimization and Maximization of Convex Functions, The Method of Steepest Descent, Newton’s Method

10

9.1-9.4

Modified Newton’s Method, Construction of the Inverse, Davidon-Fletcher-Powell Method, The Broyden Family

11

10.1-10.3

Constraints, Tangent Plane, First-Order Necessary Conditions

12

 

 

13

10.5-10.6, 10.8

Second-Order Conditions, Eigenvalues in Tangent Subspace, Inequality Constraints

14

12.1-12.3

Penalty Methods, Barrier Methods, Properties of Penalty and Barrier_Functions

15

14.1-14.2,14.4

Quadratic Programming, Direct Methods, Modified Newton’s Methods