SYSC-5004 and SYSC-3200 aim to equip the student with a set of general-purpose tools for solving common problems in engineering, industry, and business. SREE-4002 introduces the student to the kinds of trade-offs that must be made in choosing among energy supply options.

**SYSC-5004 Optimization for Engineering Applications ***(graduate)*

*Summary:* This course is
about solving the kinds of problems that occur frequently in engineering,
business, and industry. It concentrates specifically on problems of *optimization*,
which are also frequent in graduate theses in engineering, computer science,
and mathematics. Examples of thesis topics involving optimization include
numerous types of VLSI design problems (e.g. sizing of transistors to minimize
space or power consumption subject to constraints on signal propagation time),
transportation planning (e.g. scheduling operators for a transit system),
communications systems design (e.g. routing signals, power control for mobile
phones, assigning tasks to DSP processors), etc.

The goal of the course is to equip the student with the main tools of practical optimization so that they will be able to recognize an optimization problem when they encounter it in their thesis or career, and will know how to formulate and solve the problem. The emphasis is on practicality, i.e. actually solving problems using software, with sufficient theory to understand how the methods work and can be extended. The methods are presented in a more algorithmic than mathematical way, and practice is obtained via assignments which are tiny cases.

Note that the course should also interest those whose main focus is Artificial Intelligence for three reasons. (1) many AI methods have their roots in optimization, so a knowledge of optimization is useful, (2) it is important to know when to use a fast and exact optimization method instead of a slower and less exact AI method, and (3) the overlap between these two topic areas is extensive (e.g. genetic algorithms, tabu search, heuristic search).

*Topics:* A brief list of
topics is given below. Note that "programming" as in "linear
programming" is an old use of the word to mean "planning". There
is no actual computer programming done in the course; students run existing
software to solve the assignments.

- linear programming, including sensitivity analysis
- networks: shortest route, minimum spanning tree, max flow and min cut, network flow programming, assignment problem, transportation problem, etc.
- PERT and resource levelling
- integer and mixed-integer programming via branch and bound
- genetic algorithms
- dynamic programming
- nonlinear programming

**SYSC-3200 Industrial Engineering (***undergraduate***)**

*Summary:* This course is
about solving the kinds of problems that frequently occur in engineering,
industry, and business. For example, imagine that you are working in a plant that
produces computer chips or telephone equipment. A typical problem might involve
deciding the mix of products to manufacture to maximize your profits, or how to
schedule the manufacturing process so that the products are delivered on time.
Or your job may be to find the best way to route signals through a complicated
computer network. Etc., etc.

The course provides useful tools for solving a very wide range of such practical problems, tools which will be useful no matter which industry you enter or career path you choose. It is an excellent choice as an Engineering Elective for all disciplines, but especially electrical and computer systems engineering where complex problems of routing, scheduling, and assignment are particularly common.

SYSC-3200 is a required course in the Civil Engineering Concentration in Management. A similar course (perhaps titled "Operations Research" or "Management Science") is usually a requirement in any business or MBA program.

The emphasis is on understanding the methods, and on being able to use them to formulate and solve problems, which are stated as tiny cases. There is no computer programming per se, but students will use existing computer programs to carry out calculations to solve problems.

*Topics:* A brief list of
topics is given below. Note that "programming" as in "linear
programming" is an old use of the word to mean "planning". As
explained above, there is no actual computer programming done in the course.

- linear programming
- network models: shortest route, minimum spanning tree, max flow and min cut, network flow programming
- PERT for project management
- integer programming
- mixed integer programming
- genetic algorithms
- dynamic programming
- markov chain and queueing models
- inventory models

**SREE-4002 The Energy Economy, Reliability, and Risk** (*undergraduate*)

This course is an overview of topics that affect decisions about energy supply and technology options, placing sustainable and renewable energy sources and technologies within the larger context of policy choices that must be made at the societal and political levels. The goal is to provide the technical data and analytic tools that will enable engineers to help shape practical energy policies. Major themes include (i) an inventory of the supply and demand and technologies for all energy forms, including fossil fuels, nuclear, and renewable (ii) economics and analytic tools, and (iii) analysis of proposed options and policies.

For details on the current course offerings, visit the Systems and Computer Engineering “Course Materials” web page at http://www.sce.carleton.ca/dept/sce.php/courseList.