ENCE 667 Project Performance Measurement
Course Syllabus
Course Description
Examination of various techniques and models used to measure the performance of projects. Topics will include: critical path method (CPM), Program Evaluation Review Technique (PERT), Gantt charts, project crashing, resource management, capital allocation, forecasting, hypothesis testing, regression analysis, learning curve analysis, goal programming, Monte Carlo simulation, the Analytic Hierarchy Process (AHP), Pareto optimality and tradeoff curves as well as basics in linear programming and uncertainty modeling.
Course Prerequisites
- ENCE 302 Probability and Statistics for Civil Engineers or some exposure to probabilistic modeling
- MATH 240 Introduction to Linear Algebra or some exposure to vectors and matrices
- MATH 140, Calculus I or equivalent
Required Course Texts:
- BADIRU
Comprehensive Project Management Integrating Optimization Models, Management Principles, and Computers, Adedeji B. Badiru, and P. Simin Pulat - WINSTON
Operations Research Applications and Algorithms by Wayne L. Winston (Fourth Edition)
Course Objective
Provide overview of techniques and models used in measuring the performance of projects.
Instructor
Dr. Steven A. Gabriel
Office EGR 1143
Telephone (301) 405-3242; Fax: (301) 405-2585
sgabriel@umd.edu
Grading
The overall course grade will be derived from four areas:
- Weekly homeworks
- two pre-announced in-class exams
- projects
The distribution of the grade will be as follows:
- Homeworks 20%
- max{exam #1 score, exam #2 score} 30%
- min{exam #1 score, exam #2 score} 20%
- Projects (proposal, mid-term meeting, presentation, report) 30%
Course Policies
Students are encouraged to attend all lectures since the take-home exam and the homeworks will be closely related to material discussed in lectures.
It is assumed that students will complete the homeworks by themselves although casual discussion with other class members is allowed. Homeworks will generally be given out each week and due at the start of class one week later, no late homeworks will be accepted unless it’s a family or medical emergency.
The course is subject to the Code of Academic Integrity available on the web. The Code prohibits students from cheating on exams, plagiarizing papers, submitting the same paper for credit in two courses without authorization, buying papers, submitting fraudulent documents, and forging signatures.
The University has a legal obligation to provide appropriate accommodations for students with disabilities. Please inform Dr. Gabriel of any accommodations needed relative to disabilities. Also, University of Maryland policy states that students should not be penalized due to observances of their religious beliefs. Please inform Dr. Gabriel of such instances well in advance so that appropriate steps can be taken.
Short Bio on Dr. Gabriel
Academic Experience: Besides teaching at University of Maryland, Dr. Gabriel has held appointments in the Mathematical Sciences Department at The Johns Hopkins University, and in the Engineering Management and Systems Engineering Department at The George Washington University. In addition, he has served as a postdoctoral researcher in the Mathematics and Computer Science Division at Argonne National Laboratory.
Industry Experience: Dr. Gabriel has over 15 years of industry experience involving mathematical modeling of engineering-economic systems with applications in energy, transportation, service performance, and operations management. His specialties include optimization/equilibrium modeling, econometrics, decision support systems, and software development. His most recent industry experience includes 5 years as a Project Manager at ICF Consulting (www.icfconsulting.com) involving projects with their oil and gas group (www.icf-oilandgas.com) as well as their electrical power group.
ENCE667 home | Syllabus | Schedule & Homeworks | Projects | Downloads & Links
