Handbook 1996 : Faculty of Science (Volume 4 page 211)
Mathematics subject : Next:618-262 | Prev:618-252 | Search | Help
618-261 "Linear Programming and Optimization" appears differently in several places - choose the one you want:
1. Mathematics, Faculty of Science (v4, p211) : Next:618-262 | Prev:618-252
Credit points: 12.0
Coordinator: Dr M Sniedovich
Prerequisite: Mathematics 618-101 and 618-102 (1995 Handbook), or 618-121 and 618-122, or 618-200, or 618-211, or 618-100, 618-101, 618-130, with concurrent enrolment in 618-200, or 618-141, 618-142, 618-130, with concurrent enrolment in 618-200; 618-231 is also desirable.
Contact: 39 lectures (three a week)
Timetable: First semester
Objectives:
On completion of this subject, students should:Comprehend:
- the essential features of optimization problems encountered in operations research investigations; what kind of practical problems have these features;
- a number of basic mathematical techniques used to solve linear and nonlinear optimization problems;
- the theoretical foundations of these techniques; the essential role that computers play in the analysis and solutions of operations research problems.
Have developed:
- basic skills required to construct formal mathematical models for practical optimization problems;
- skills needed to solve linear programming problems with the aid of the simplex method and to assess the results;
- skills to make use of the relationship between primal and dual problems and their respective optimal solutions;
- skills in using dynamic programming techniques in the solution of a number of problem-areas;
- skills in deriving and analysing necessary and sufficient optimality conditions pertaining to classical nonlinear optimization problems.
Appreciate:
- the extent and limitations of a number of operations research techniques such as linear programming, dynamic programming and classical first and second order analysis as far as solving practical real-world optimization problems is concerned;
- the important role that linear algebra and calculus play in the development of these techniques;
- why computers are so important in solving real-world optimization problems of the operational research type.
Content:
Linear programming:linear programming, simplex and revised simplex methods, sensitivity analysis; formulation of optimisation problems; transportation problems; use of computer packages on the Macintosh. Optimisation:optimisation of functions of several variables, constraints, Lagrange multipliers; other operations research techniques, including critical path, and some dynamic programming models; applications in economics and management; use of computer packages on the Macintosh.
Assessment:
Up to 26 pages of written assignments and up to three hours of end-of-semester written examination.
1. Mathematics, Faculty of Science (v4, p211) : Next:618-262 | Prev:618-252
2. Math. & Stats., Faculty of Educ(Parkville) (v5, p147) : Next:618-262 | Prev:618-252
Note: It is not possible to gain credit for both 618-261 and the Mathematical Sciences subject 617-261 taught in previous years.
Credit points: 12.0
Coordinator: Dr M Sniedovich.
Prerequisite: Mathematics 618-101 and 618-102 (1995 Handbook), or 618-121 and 618-122, or 618-200, or 618-211, or 618-100, 618-101, 618-130, with concurrent enrolment in 618-200, or 618-141, 618-142, 618-130, with concurrent enrolment in 618-200; 618-231 is also desirable.
Contact: 39 lectures (three each week)
Timetable: First semester.
Objectives:
On completion of this subject, students should:Comprehend:
- the essential features of optimization problems encountered in operations research investigations; what kind of practical problems have these features;
- a number of basic mathematical techniques used to solve linear and nonlinear optimization problems;
- the theoretical foundations of these techniques; the essential role that computers play in the analysis and solutions of operations research problems.
Have developed:
- basic skills required to construct formal mathematical models for practical optimization problems;
- skills needed to solve linear programming problems with the aid of the simplex method and to assess the results;
- skills to make use of the relationship between primal and dual problems and their respective optimal solutions;
- skills in using dynamic programming techniques in the solution of a number of problem-areas;
- skills in deriving and analysing necessary and sufficient optimality conditions pertaining to classical nonlinear optimization problems.
Appreciate:
- the extent and limitations of a number of operations research techniques such as linear programming, dynamic programming and classical first and second order analysis as far as solving practical real-world optimization problems is concerned;
- the important role that linear algebra and calculus play in the development of these techniques;
- why computers are so important in solving real-world optimization problems of the operational research type.
Content:
Linear programming Linear programming, simplex and revised simplex methods, sensitivity analysis; formulation of optimisation problems; transportation problems; use of computer packages on the Macintosh. Optimisation Optimisation of functions of several variables, constraints, Lagrange multipliers; other operations research techniques, including critical path, and some dynamic programming models; applications in economics and management; use of computer packages on the Macintosh.
Assessment:
Up to 26 pages of written assignments and up to three hours of end-of-semester written examination.
* Note that CONTACT, CONTENT, NOTE differs from the maintainer's version above. A log of variations is available.
2. Math. & Stats., Faculty of Educ(Parkville) (v5, p147) : Next:618-262 | Prev:618-252
Status: Official 1996 Date created: Oct 9 1995 Last modified: Oct 9 1995 Authorised by: Academic Registrar Email enquiries: Course_Information@registrar.unimelb.edu.au
Maintained by: Dept. of Mathematics, Faculty of Science.
Copyright © University of Melbourne 1995,1996.