Tentative Topics

1.      Introduction to complexity theory

2.      Heuristic, Dichotomous Search, and Neighborhood search

3.      Greedy Random Adaptive Search Procedure

4.      Simulated Annealing Algorithm

5.      Genetic Algorithm

6.      Tabu Search

7.      Scatter Search

8.      Bio-Inspired Algorithm – Ant Colony Optimization and Artificial Neural Network

9.      Agent Based Modeling and Optimization

10.  Simulation and Optimization

11.  Advanced Topics and Recent Trend

12.  Application and Presentations

* Topic may vary depends on the availability of time and interests of students

 

List of papers or publications

Introduction and Computational complexity

[1]               C. Tovey, (2002) "Tutorial on Computational Complexity,” Interfaces, Vol. 32, No. 3, pp. 30-61.

Neighborhood Search Heuristics and Meta-Heuristics

[2]               C. R. Reeves, (1993) “Modern Heuristic techniques for Combinatorial Problems,” John Wily & Sons, New York, NY. 

GRASP – Semi-Greedy and Sampling

[3]               J.P. Hart and A.W. (1987) Shogan Semi-greedy Heuristics: An Empirical Study. Operations Research Letters, 6:107–114.

[4]               T.A. Feo and M.G.C. Resende (1989) A Probabilistic Heuristic for a Computationally Difficult Set Covering Problem. Operations Research Letters, 8:67–71.

[5]               T.A. Feo and M.G.C. Resende (1995) Greedy Randomized Adaptive Search Procedures.  J. of Global Optimization, 6:109–133, 1995.

[6]               L. Pitsoulis and M.G.C. Resende (2002) Greedy randomized adaptive search procedures. In P.M.Pardalos and M.G.C.Resende, eds, Handbook of Applied Optimization, pp. 168–181, Oxford University Press.

[7]               M.G.C. Resende and C.C. Ribeiro (2003) Greedy Randomized Adaptive Search Procedures. In F. Glover and G. Kochenberger, eds, Handbook of Metaheuristics, pp. 219–249, Kluwer Academic Publishers, 2003.

[8]               P. Festa and M.G.C. Resende (2002) GRASP: An Annotated Bibliography. In C.C. Ribeiro and P. Hansen, editors, Essays and Surveys on Metaheuristics, pp. 325–367, Kluwer Academic Publishers, 2002.

 

Simulated Annealing

[9]               S. Kirkpatrick and C. D. Gelatt and M. P. Vecchi, Optimization by Simulated Annealing, Science, Vol 220, Number 4598, pages 671-680, 1983.

[10]           R. W. Eglese, (1990), Simulated Annealing – A Tool for Operations Research,  European Journal of Operational Research, 46: 271-281

[11]           C. Koulamas, S. R. Antony, and R. Jaen. A Survey of Simulated Annealing Applications to Operations Research Problems. Omega International Journal of Management Science, 22(1):41–56, 1994.

[12]           B. Suman and P. Kumar, (2006) A survey of simulated annealing as a tool for single and multiobjective optimization, Journal of Operational Research Society, 57:1143-1160.

[13]           W.C. Chiang and R. Russell, (1996) “Simulated Annealing Metaheuristics for the Vehicle Routing Problem with Time Windows, Annals of Operations Research, 63:3-27.

Genetic Algorithm (1) (2) (3)

[14]           D. Whitley, A Genetic Algorithm Tutorial, Computer Science Department Colorado State University, CO, http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf

[15]           C. L. Reeves, (1997) Genetic Algorithm for the Operations Researcher, INFORMS Journal of Computing,  9:3 231-250

[16]           J. Beasley and P.C. Chu (1996) A Genetic Algorithm for the Set Covering Problem. European Journal of Operational Research, 94(2), 393–404.

[17]           J. Beasley and P.C. Chu (1998) A Genetic Algorithm for the Multi-Dimension Knapsack Problem, Journal of Heuristics 4, 63-86

[18]           Mitchell, Melanie, (1996), An Introduction to Genetic Algorithms, MIT Press, Cambridge, MA.

Tabu Search (1) (2)

[19]           Glover, F. and M. Laguna. (1997).  Tabu Search.  Kluwer, Norwell, MA.

[20]           Glover, F. "Tabu Search — Part I", ORSA Journal on Computing 1989 1: 3, 190-206.

[21]           Glover, F. "Tabu Search — Part II", ORSA Journal on Computing 1990 2: 1, 4-32.

[22]           Battiti, R. and G. Tecchiolli (1994), “The Reactive Tabu Search”, ORSA Journal on Computing 6, 126-140.

[23]           Gendreau, M., A. Hertz and G. Laporte (1994), “A Tabu Search Heuristic for the Vehicle Routing Problem”, Management Science 40, 1276-1290.

[24]           Glover, F. (1992), “Ejection chains, Reference Structures and Alternating Path Methods for Traveling Salesman Problems”, University of Colorado.  Shortened version published in Discrete Applied Mathematics 65, 223-253, 1996.

[25]           Gendreau, M. (2002), “Recent Advances in Tabu Search”, in Essays and Surveys in Metaheuristics, C.C. Ribeiro and P. Hansen (eds.), Kluwer Academic Publishers, pp. 369-377.Retrieved from "http://en.wikipedia.org/wiki/Tabu_search"

Scatter Search

[26]           F. Glover, M. Laguna and R. Martí, (2003) Scatter Search, Advances in Evolutionary Computation: Theory and Applications, A. Ghosh and S. Tsutsui (Eds.), Springer-Verlag, New York, pp. 519-537 (2003)

[27]           M. Laguna, Scatter Search,  In Handbook of Applied Optimization, P. M. Pardalos and M. G. C. Resende (Eds.), Oxford University Press, pp. 183-193 (2002)

[28]           F. Glover, M. Laguna and R. Martí , (2000) Fundamentals of Scatter Search and Path Relinking, Control and Cybernetics, vol. 39, no. 3 pp. 653-684 (2000)

 Ant Colony Optimization, Swarm Intelligence, Partical Swarm, Harmony Search

[29]           M. Dorigo & T. Stützle, 2004. Ant Colony Optimization, MIT Press

[30]           M. Dorigo & L. M. Gambardella, 1997. "Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem". IEEE Transactions on Evolutionary Computation, 1 (1): 53–66.

[31]           E. Bonabeau, M. Dorigo et G. Theraulaz, 1999. Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press

[32]           A. P. Engelbrecht. Fundamentals of Computational Swarm Intelligence. Wiley, 2005.

[33]           Haykin, S. (1999) Neural Networks: A Comprehensive Foundation, Prentice Hall

[34]           “An Online Textbook on Neural Networkhttp://www.statsoft.com/textbook/stneunet.html

Simulation and Optimization

[35]           F. Azadivar, (2004), “A Tutorial on Simulation Optimization ,”Winter Simulation Conference. 198-204

Local Search for General Integer Program -- NSIP

[36]           Fischetti, M., & Lodi, A. (2003). Local Branching. Math. Programming: Series B, 98, 23-47.

Advanced Topics, Recent Trend and Applications

[37]           Osman, I.H. and J.P. Kelly (eds.) (1996), Meta-Heuristics: Theory and Applications, Kluwer Academic Publishers, Norwell, MA.

 

Sample Code:

Sample code for dichotomous search, simulated annealing, genetic algorithm, tabu search, scatter search for problems such as vehicle routing will be provided.