Metaheuristic OR670/SYST670/OR750
Instructor: Dr. Rajesh Ganesan
Office: Engr Building, Room 2217
Phone: (703) 993-1693
Fax: (703) 993-1521
Email: rganesan@gmu.edu
https://link.springer.com/book/10.1007/978-1-4419-0910-7 Planning and Scheduling in mfg and service M Pinedo - 2nd ed
https://itslearningakarmazyan.files.wordpress.com/2015/09/operation-research-aplications-and-algorithms.pdf Winston's book for OR 541/2
https://link.springer.com/content/pdf/10.1007%2F978-3-319-07124-4.pdf Hand Book of Heuristics Marti, Rafael et al.
https://www.researchgate.net/file.PostFileLoader.html?id=5703bd8e4048546d0943c349&assetKey=AS%3A347504454455296%401459862926298 METAHEURISTICS FROM DESIGN TO IMPLEMENTATION Talbi
Week 1
Computational complexity
Week 2
S-metaheuristics
Metaheuristics Implementation: Binary local search - function maximization excel examples
Week 3
Tabu search - Examples: function maximization, Knapsack, TSP, set covering
Single machine scheduling - 1 machine n jobs,
Parallel Machines - m identical machines n jobs with parallel machines (job visits only 1 machine),
Flow Shop - conveyor lines (jobs flow through all machines)
job - task- trainee
machine - resource- department
Week 4
Simulated Annealing, examples- function maximization, job shop scheduling. knapsack
Chapter 1-3 review - definitions, constarints, objective functions
Week 5
Multi-start search, ILS, GRASP-greedy randomized adaptive search procedure , VNS, GLS notes 4
- minimum spanning tree
-capacitated minimum spanning tree with GRASP
Chapter- 4 CPM, PERT, Time/Cost tradeoff heuristics
Week 6
Dispatching rules - page 442 of text
ATC and ATCS - Page 446 of text
Week 7
Chap 5 Job shop scheduling - Shifting Bottleneck Heuristics notes 5 min(makespan) objective
Solution for min(makespan)
Shifting bottleneck with weighted tardiness objective (in the 1st edition of Pinedo's book)
Machine sequence must be found
Week 8
Chapter 6 notes 6 machines are already positioned along the flexible assembly flow line. Machine sequence is not there
Flexible assembly flow lines - scheduling paced and unpaced lines with and without buffer
Minimum part set MPS (jobs in a MPS do not repeat within the cycle)
Profile fitting for unpaced lines -obj is min cycle time (max throughput). determine job seq
GS - Grouping and Spacing - conveyor belt moves at fixed speed (cycle time is fixed). multiple obj: min set up costs, weighted tardiness, spacing costs. Also determine job seq
FFLL - Flexible flow line loading heuristic FFLL excel minimize (max overload) obj is min cycle time (max throughput) determine job seq
Week 9
Chapter 7
Lot sizing and sequencing notes
Focus on economic order quantity (EOQ), inventory costs, set up time and set up costs. Sequencing and batching size (NOT MPS) to be determined which sets the cycle time. No machine sequence. determine job seq for sequence dependent set-up time with a standard heuristic like Tabu or SA
(jobs in a batch can repeat within a cycle)
FFS Frequency fixing and sequencing heuristic example - Does sequencing too. No need for a standard heuristic like Tabu or SA
Tradeoffs between cycle time and total costs
Tradeoffs between inventory holding costs and set-up costs
Chapter 8 SCM - (self read)
Week 10
P-metaheuristics notes
GA example excel (refer handout for the problem)
Week 11
Scatter search, EDA.
Genetic Programming, Ant colony optimization notes
PSO
Bee colony and AIS notes
Week 12
Chapter 9 Reservation and Timetabling notes
Reservation without slack heuristic ( Max # of activities assigned to resource i)
Reservation without slack heuristic (Min # of resources needed)
Reservation with slack heuristic (Max weighted # of activities)
First Fit (FF) - timetabling with workforce constraint
FFD First Fit Decreasing
Graph coloring heuristic- timetabling with operator or tooling constraint
Week 13
Chapter 9
Timetabling with cost minimization
Timetabling with both resource and tooling constraints -Project scheduling - workforce, tooling, unequal processing times, and with precedence constraints (requires a combination of heuristics)
Chapter 10
Timetabling in sports
Chapters 11 and 12. No new heuristics.Mostly integer programmning, which could be replaced by other standard heuristics.
Week 14
Chapter 13
Workforce scheduling notes
Days off scheduling
Shift and Cyclic scheduling
Crew Scheduling
Multi-obj optimization, hybrid and parallel metaheuristics notes
Exams and Project
Midterm Due DEC 6 or earlier
Project Due Dec 6
Final Exam Due Dec 6 - for problem 4 you could restrict a flight to a max of 2 cities.
Heuristics list:
S- Metaheuristics
1. Binary local search
2. Tabu search
3. Simulated Annealing
4. Multi-start search
5. ILS - Iterative local serch
6.GRASP-greedy randomized adaptive search procedure
7. VNS - variable neighborhood search
8. GLS- guided local search
Appendix C of text
9. Several Dispatch rules
10.Composite dispatch rules - ATC and ATCS - 1 m/c n jobs scheduling with set up time
11. Beam search as a quick alternative to branch and bound - Ex from text.
Chapter 4
12. PERT
13. CPM - Ex from text.
14. Time/Cost tradeoff heuristics -Ex from text.
Chapter 5
15. Shifting Bottleneck heuristics - m m/c- n jobsj-ob shop with precedence constraints-makespan obj fnc Ex from text.
16. Shifting Bottleneck heuristics - m m/c- n jobsj-ob shop with precedence constraints-weighted tardiness obj fnc Ex from handout
Chapter 6
17.
Unpaced flexible assembly lineProfile fitting heuristic (PF)
18.
Paced flexible assembly lineGrouping and Spacing Heuristic (GS)
19.
Flexible Flow systems with Bypass - Flexible flow line loading algorithm is used
(FFLL)
Chapter 7
Rotation Schedules
20. 1 machine 1 job - EOQ
21. 1 machine n jobs EOQ without set up times
22. 1 machine n jobs EOQ with set up times
23. FFS heuristics - Frequency fixing and sequencing without set up time
24. FFS heuristics - Frequency fixing and sequencing with set up time
P-Metaheuristics
25. GA - Genetic Alg
26- Scatter search
27. Estimation of Distribution (EDA) Alg
28. Genetic Programming
29. Ant Colony Optimization
30. PSO -particle swarm opt
31. Bee Colony opt
32. Artificial immume system
Chapter 9
33) Reservation without slack heuristic ( Max # of activities assigned to resource i)
34) Reservation without slack heuristic (Min # of resources needed)
35) Reservation with slack heuristic (Max weighted # of activities)
36) First Fit (FF) - time tabling with workforce constraint
37) FFD First Fit Decreasing
38) Graph coloring heuristic- time tabling with operator or tooling constraint
39) time tabling with cost minimization
40) project scheduling - workforce, tooling, unequal processing times, and with precedence constraints (requires a combination of heuristics)
Chapter 10
41) Single and double round robin heuristic
Chapter 13
42) Days-off scheduling heuristic
43) Crew scheduling heuristic