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15.066

System Optimization and Analysis for Operations

4-0-8 units · Graduate

Introduction to mathematical modeling, optimization, and simulation, as applied to manufacturing and operations. Specific methods include linear programming, network flow problems, integer and nonlinear programming, discrete-event simulation, heuristics and computer applications for manufacturing processes, operations and systems. Restricted to Leaders for Global Operations students.

Summer 2003 · System Optimization and Analysis for Manufacturing

Topics

  • Introduction and Overview
  • LP (Linear Programming) - Introduction, Formulations and Geometry
  • LP (Linear Programming) - Example
  • Tutorial
  • Networks - Introduction
  • LP (Linear Programming) - Example: Tony Palumbo, Ford
  • LP (Linear Programming) - Solution Methods and Sensitivity Analysis
  • Integer Programming - Formulations
  • Integer Programming - Algorithms
  • Integer Programming - Heuristics
  • Debriefing of Inventory Simulation (with 15.761 )
  • Stochastic LP (Linear Programming)
  • Optimization in Practice: John Bean, Intel
  • Introduction, Simulation Process and Stochastic Modeling
  • Monte-Carlo Theory and Examples (with Crystal Ball®)
  • Tutorial: Monte-Carlo Modeling and Crystal Ball® Tutorial
  • Ontario Gateway Case Discussion
  • Discrete-Event Framework and Examples (with SIMUL8®)
  • Theory of Constraints (Joint Session with 15.761 )
  • Tutorial: Discrete-Event Modeling and SIMUL8® Tutorial
  • Discrete-Event Case Discussion
  • Experimental Design and Simulation Analysis
  • Advanced Modeling, Simulation-Based Optimization
  • Tutorial: Experimental Design and Simulation Analysis Tutorial
  • Non Linear Programming - Formulations
  • NLP (Non Linear Programming) - Examples and Algorithms
  • Project Presentations
  • Project Presentations and Class Summary

Readings

  • Some readings refer to sections of the course textbook, which is Baker, Kenneth R., Optimization: A Spreadsheet-Based Approach, Duxbury Press, 2003.
    Listed reading
  • WEEK #: 1 · SES #: 1 · TOPICS: Introduction and Overview · READINGS: Baker: 1 & 2.1 - 2.19
    Reading assignment
  • SES #: 2 · TOPICS: LP (Linear Programming) - Introduction, Formulations and Geometry · READINGS: Baker: Appendix 2A
    Reading assignment
  • SES #: 3 · TOPICS: LP (Linear Programming) - Example · READINGS: Red Brand Case: Wilson, Robert B. Red Brand Canners . Stanford University, 1965. Available through Harvard Business School Publishers, Case No. OSA1.
    Reading assignment
  • WEEK #: 2 · SES #: 4 · TOPICS: Networks - Introduction · READINGS: Baker: 3
    Reading assignment
  • Polaroid Example: Tactical Shipping and Scheduling at Polaroid with Dual Lead-Times ( PDF ) - Paper courtesy of Kermit Threatte and Stephen C. Graves, October, 2001. Used with permission. ↗
    Listed reading
  • SES #: 5 · TOPICS: LP (Linear Programming) - Example · READINGS: Filatoi Riuniti Case: at the end of Chapter 7 in Bertsimas, D., and R. Freund. Data Models, and Decisions: The Fundamentals of Management Science . Southwestern College Publishing, 2000.
    Reading assignment
  • WEEK #: 3 · SES #: 6 · TOPICS: LP (Linear Programming) - Example: Tony Palumbo, Ford · READINGS: Ford Case: Carmelo Anthony Palumbo under the direction of Stephen C. Graves. Ford Pan-European Durable Containers . MIT Leaders for Manufacturing Program, 2002.
    Reading assignment
  • SES #: 7 · TOPICS: LP (Linear Programming) - Solution Methods and Sensitivity Analysis · READINGS: Baker: 5
    Reading assignment
  • WEEK #: 4 · SES #: 8 · TOPICS: Integer Programming - Formulations · READINGS: Baker: 6.1 - 6.27
    Reading assignment
  • SES #: 9 · TOPICS: Integer Programming - Algorithms · READINGS: Baker: 6.28 - 6.33
    Reading assignment
  • SES #: 10 · TOPICS: Integer Programming - Heuristics · READINGS: Baker: 8 (Skim)
    Reading assignment
  • SES #: 12 · TOPICS: Stochastic LP (Linear Programming) · READINGS: Baker: 2.20 - 2.26
    Reading assignment
  • Red Brand (B) Case: Wilson, Robert B. Red Brand Canners (B) . Stanford University, 1965. Available through Harvard Business School Publishers, Case No. OSA1.
    Listed reading
  • WEEK #: 6 · SES #: 14 · TOPICS: Introduction, Simulation Process and Stochastic Modeling · READINGS: Simulation Module Outline ClearPictures, Inc.
    Reading assignment
  • SES #: 15 · TOPICS: Monte-Carlo Theory and Examples (with Crystal Ball®) · READINGS: Probability/Statistics Review 1
    Reading assignment
  • WEEK #: 7 · SES #: 16 · TOPICS: Ontario Gateway Case Discussion · READINGS: Ontario Gateway: at the end of Chapter 5 in Bertsimas, D., and R. Freund. Data Models, and Decisions: The Fundamentals of Management Science . Southwestern College Publishing, 2000.
    Reading assignment
  • SES #: 17 · TOPICS: Discrete-Event Framework and Examples (with SIMUL8®) · READINGS: Introduction to SIMUL8® (Adapted for 15.066J from some of SIMUL8 Corporation’s training material.)
    Reading assignment
  • Discrete-Event Case: Human Genome Project ( PDF ) - Paper courtesy of Jérémie Gallien and Scott A. Rosenberg, MIT Sloan School of Management, 2003. Used with permission. ↗
    Listed reading
  • SES #: 20 · TOPICS: Experimental Design and Simulation Analysis · READINGS: Probability/Statistics Review 2
    Reading assignment
  • WEEK #: 9 · SES #: 22 · TOPICS: Non Linear Programming - Formulations · READINGS: Baker: 7
    Reading assignment
  • SES #: 23 · TOPICS: NLP (Non Linear Programming) - Examples and Algorithms · READINGS: DeWitt, Charles. Apollo Paper Company case study. MIT Sloan School of Management. Unpublished.
    Reading assignment
  • Baker, Kenneth R. Optimization: A Spreadsheet-Based Approach. Duxbury Press, 2003.
    Listed reading
  • The textbook is not yet published but the author and publisher have granted us permission to use the manuscript, based on our commitment to provide some feedback. As the name suggests, the textbook will cover optimization topics. For the simulation component of the class, we will distribute readings and notes.
    Listed reading
  • Introduction to Mathematical Programming , by W. L. Winston, PWS Kent, 1995, which does a great job on algorithms and model formulations;
    Listed reading
  • Practical Management Science , by W. L. Winston and S. C. Albright, Duxbury, second edition, 2001, which is excellent in describing a wide range of applications as well as illustrating spreadsheet modeling;
    Listed reading
  • The Science of Decision Making , by E. V. Denardo, Wiley 2002, which was used last year and provides a problem-based approach both to optimization as well as probability applications;
    Listed reading
  • and Data, Models, and Decisions: The Fundamentals of Management Science , by D. Bertsimas and R. Freund, South-Western College Publishing, 2000, which was written for the Sloan MBA core class in Data, Models and Decisions. Indeed, we will use some of the cases and other material from this book.
    Listed reading

Prerequisites & course information

Same subject as 2.851[J] Prereq: Calculus II (GIR) G (Summer) 4-0-8 units

Sources