20297 Deterministic Models in Operations Research 1

Credits: 6 intermediate credits in Mathematics

Prerequisites: none

Required: One of the following: Mathematics for Students of Social Sciences, Linear Algebra for Natural Science Students, Linear Algebra I

The course, based on a translation (by Varda Lev) of chapters 1-11 of Introduction to Mathematical Programming, by F.S. Hillier and G.J. Lieberman (McGraw-Hill, 1990), was developed by Zippy Erlich and Hannah Clavner.

The course acquaints students with problem-solving methods using deterministic models in operations research. Operations research is a mathematical approach to decision-making and optimization problems in many fields. The conventional approach of operations research is based on the design of a mathematical model describing the problem or a close approximation thereof, and the development of algorithms for the search of optimal solutions. Examining the model and analyzing the solutions assists in optimal decision-making.

Topics: Introduction; Overview of modeling; Introduction to linear programming; Solving linear programming problems: The simplex method; The theory of the simplex method; Duality theory and sensitivity analysis; Special types of linear programming problems; Formulating linear programming models, including goal programming; Other algorithms for linear programming; Network analysis, including Pert/Cpm; Dynamic programming.

1There is some overlap in the content of this and other courses. For details, see Overlapping Courses.