ECE 307 - Techniques for Engineering Decisions

Summer 2009 | Fall 2009 | Spring 2010 | Summer 2010

Course Prerequisites	Credit in ECE 210 Credit or concurrent registration in ECE 313
Course Directors	George Gross
Description	This course is concerned with modeling of decisions and analysis of models to develop a systematic approach to making decisions. This course introduces probability theory as the fundamental mathematical basis for the development of techniques for solving typical problems faced in making engineering decisions in industry and government. The aim of this course is to teach students to think structurally about decision-making problems. Extensive use of case studies gets students involved in real world situations.
Credit	3 hours
Goals	Nature of engineering decisions; structuring of decisions; role of models; interplay of economics and technical/engineering considerations; decision making under certainty and uncertainty; good decisions vs. good outcomes; tools Resource allocation decision making using the linear programming framework; problem formulation; duality; economic interpretation; sensitivity analysis; interpretation of results Scheduling and assignment decisions using network flow concepts; transshipment problem formulation and solution; application to matching decisions; network optimization; scheduling application Sequential decision making in a dynamic programming framework; nature of dynamic programming approach; problem formulation; solution procedures Probability theory; random variables; probability distributions; expectation; conditional probability; moments; convolution Statistical concepts; data analysis; statistical measures; estimation Application of probabilistic concepts to the modeling of uncertainty in decision amking; modeling of the impacts of uncertainty; application to siting, investment and price volatility problems Decision making under uncertainty; decision trees; value of information; uses of data; sensitivity analysis and statistics
Topics	Decision topics include research allocation, logistics, scheduling, sequential decision making, siting of facilities, investment decisions and other problems for decision making under uncertainty. Resource allocation decision making using the linear programming framework: problem formulation; basic approach; duality; economic interpretation; sensitivity analysis; interpretation of results Scheduling and assignment decisions using network flow concepts: trans-shipment problem formulation and solution; application to matching decisions; network optimization; scheduling applications Sequential decision making in a dynamic programming framework: nature of dynamic programming approach; problem formulation; solution procedures; key limitations Probability theory: random variables; probability distribution; expectation; conditional probability; moments; convolution Statistical concepts: data analysis; statistical measures; estimation Application of probabilistic concepts to the modeling of uncertainty in decision making: modeling of the impacts of uncertainty; applications to siting, investment and price volatility problems Decision making under uncertainty: decision trees; value of information; uses of data; sensitivity analysis and statistics Case Studies
Course Prerequisites	ECE 210; credit or concurrent registration in ECE 313.