Introduction to Optimization Methods

Fall 2012

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 Risk Solver Platform software.

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 Risk Solver Platform.
  • Find solutions to optimization problems using the most appropriate algorithm and settings in Risk Solver Platform.
  • Perform sensitivity analysis by tracing the effects of varying a parameter on the optimal decision variables and the objective function.

Instructor

Professor Kenneth Baker
Buchanan 102
Kenneth.R.Baker@Dartmouth.EDU

Textbook

Optimization Modeling with Spreadsheets (Second Edition), K. Baker, published by John Wiley & Sons.

Schedule

Class Date Topic Reading Homework
1 11-Sep Introduction to Optimization Ch. 1  
2 13-Sep Basic Linear Programming Models Ch. 2 Ch1/1,2,8
3 18-Sep Case: Red Brand Canners   2/3,4
4 20-Sep Special Network Models Ch. 3.1-3.4 2/5,6,7
5 25-Sep Case: Hollingsworth Paper Co. See Ch. 3 3/1,3
6 27-Sep General Network Models Ch. 3.5-3.7 3/2,4,5,6
7 2-Oct Sensitivity Analysis Ch. 4.1-4.5 3/10,11
8 4-Oct Patterns Ch. 4.6 4/4ab,7ab
9 9-Oct Nonlinear Programming Models Ch. 8.1-8.4.2 4/4cde,5,6,13
10 11-Oct Portfolio Model Ch 8.4.3-8.5 8/1,3,7,9
11 16-Oct Integer Programming Ch. 6.1-6.3 6/1,2,3,P7
12 18-Oct Mid-Term Exam    
13 23-Oct Binary Choice Models Ch. 6.4-6.8 6/6,7,9
14 25-Oct Logical Constraints Ch. 7.1-7.3 6/5,10
15 30-Oct Location Models Ch. 7.4 7/1,3,4
16 1-Nov Traveling Salesperson Problem Ch. 7.5-7.6 7/5,6,7
17 6-Nov The Evolutionary Solver Ch. 9 7/8,9,SNE
18 8-Nov Cluster Analysis   9/1,2,3,4
19 13-Nov Review See Ch. 9 9/11,12

Blackboard

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