Introduction to Optimization Methods

Fall 2008

Course Description

Optimization deals with design and operating decisions for complex systems, and this course provides the student with a collection of optimization modeling and solution tools that can be useful in a variety of industries and functions. The main topics covered are linear programming, nonlinear programming, integer programming, and combinatorial programming. Spreadsheet models will be primary vehicles for building and solving optimization models, with emphasis placed on the use of Excel's Premium Solver.

Principal Learning Objectives

  • Translate a verbal or graphical description of a decision problem into a valid optimization model, by identifying variables, constraints, and an objective function.
  • Interpret the meaning and assess the validity of a particular optimization model.
  • Express a given optimization model in an Excel spreadsheet, structured for use with Premium Solver.
  • Find solutions to optimization problems using the most appropriate algorithm and settings in Premium Solver.
  • Perform sensitivity analysis by tracing the effects of varying a parameter on the optimal decision variables and the objective function.

Instructor

Professor Kenneth Baker
Murdough 324
Kenneth.R.Baker@Dartmouth.EDU

Textbook

The text is K. Baker, Optimization Modeling with Spreadsheets (Duxbury Press).

Schedule

Class Date Topic Reading Homework
1 25-Sep Introduction to Optimization Ch 1
2 30-Sep Basic Linear Programming Models Ch 2 Ch1/1,2,3
3 2-Oct Case: Red Brand Canners 2/3,4
4 7-Oct Special Network Models Ch 3.65-83 2/5,6
5 9-Oct Case: Hollingsworth Paper Co. Ch 3.100-103 3/1 M2.3
6 15-Oct Sensitivity Analysis Ch 4.104-127 3/2,3,4,5 M2.5a
7 16-Oct General Network Models Ch 3.83-93 4/2ab,3ab,4ab M2.4c
8 21-Oct Patterns 3/10,11 M2.7
9 23-Oct Nonlinear Programming Models Ch 7.244-269 4/4cde,5,9 M2.4a
10 28-Oct Mid-Term Exam
11 30-Oct Portfolio Model Ch 7.269-279 7/1,11,14 M3.10
12 4-Nov Binary Choice Models Ch 6.186-203 TBA M4.5
13 6-Nov Integer Formulations Ch 6.203-209 6/5,6,10
14 11-Nov Traveling Salesperson Problem Ch 6.209-219 6/7,8,9
15 13-Nov Location Models Ch 6.220-233 6/14,15,SNE
16 18-Nov The Evolutionary Solver Ch 8 6/11,12,13 M6.8
17 20-Nov Cluster Analysis 8/1,2,5,6 M6.21
18 25-Nov Case: Colgate Wave Ch 8.317-20 8/7,8 M6.13
19 2-Dec Review
Take-Home Final Exam

Blackboard

More information about this course can be found at the Blackboard site. You can login to Blackboard using your DND username and password.