MSCI 332 - Deterministic optimization models and methods

MSCI 332 builds on the material presented in MSCI 331, and explores more advanced optimization techniques and applications. Upon completion of the course, students are able to:

  • Recognize the major capabilities and limitations of deterministic optimization models and methods as applied to management engineering decision problems.
  • Formulate deterministic optimization models: objectives, decisions and constraints.
  • Describe the theory behind available solution methods and apply exact and heuristic algorithms.
  • Describe a problem related to deterministic optimization by placing it in its general context and framework.
  • Compare and contrast design solutions by assessing the validity of proposed solutions.
  • Develop an exact or heuristic solution methodology to solve a model.

Watch a former Management Engineering student describe why she loved MSCI 332!

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Assignments in MSCI 332

Assignments present students with realistic Management Engineering design problems. Students are responsible for designing models and solutions and analyzing various scenarios. They conduct this work using modelling and solving software such as R and Gurobi.

Using optimization to improve cancer treatments

For example, in one assignment, students apply advanced optimization methods to radiation therapy treatment planning. The problem they tackle is how to dose radiation to the tumor while minimizing its impact to healthy organs that surround it.

Taking a simplified 2-dimensional representation of the problem, students develop and solve a model that describes the radiation produced by the various beamlets of Beams 1 and 2 such that the tumor is hit with the correct radiation dose and the surrounding organs receive as little radiation as possible.

radiation therapy