This class will cover models and algorithms for scheduling problems. We will cover a wide range of scheduling models including single machine, multiple machine, shop environments. In each enviroment we will study a variety of scheduling problems and their solution.

Information

• Syllabus
• Course Information
• Project
• Schedule of Project Presentations

Homework

• HW 1
• HW 2
• HW 3
• HW 4
• HW 5
• HW 6
• HW 7
• HW 8
• HW 9
• HW 10

Homework Solutions

Examples

• Lecture 1
• Basic Notation
• Basics of Algorithm Analysis
• Running times of various functions
• Simple Dispatch Rules
• Reductions
• Some notes on NP-completeness.
• A list of some NP-complete problems
• Branch and bound for 1|r_j | L_max
• Minimizing late jobs
• Least Cost Last
• Total Tardiness
• Parallel Machines - Makespan
• Some notes on R|pmtn|C _max .
• Prallel Machines - Average Completion Time
• Project Scheduling
• Heuristics
• simulated annealing
• tabu search
• genetic algorithms
• Shop Scheduling
• Permutation Flow Shop
• Job Shop
• Shifting Bottleneck
• Some Shop Scheduling Bounds
• Airline Scheduling
• Scheduling in Transportation
• Stochastic Scheduling
• Gittins Index
• Energy in Scheduling
• Nuclear Weapons Scheduling
• DataCenter Scheduling

Course Announcements

• Midterm will be in class on March 14. You can bring one 8.5 by 11 inch piece of paper with writing on both sides. It will cover all material covered up to and including lecture on March 7. You can find the problems from a previous year's midterm here . Solution is here
• Final is on May 14 at 9AM.