Max-min ant system applied in economic load dispatch

WSEAS Transactions on Computers

Volumn 4, Issue 7, 2005, Pages 711-717

  Vlachos, Aristidis ^a   Moue, Aspasia ^b  

^a UNIVERSITY OF PIRAEUS   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Ant colony optimization; Economic load dispatch; Max Min ant system

Indexed keywords

ELECTRIC LOAD DISPATCHING; EVOLUTIONARY ALGORITHMS; MATHEMATICAL MODELS; OPERATIONS RESEARCH;

ANT COLONY OPTIMIZATION; ECONOMIC LOAD DISPATCH; MAX-MIN ANT SYSTEM;

OPTIMIZATION;

EID: 22944439740     PISSN: 11092750     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Guan. X. Luh, P.B. Zhang L., Nonlinear approximation method in Lagrangian relaxation based algorithms for hydrothermal scheduling, IEEE Trans. Power Systems, Vol. 10, (2), 1995, pp. 772-778.
2. Wood A.J, Wollenberg B.F, Power Generation, Operation and Control, John Wiley & Sons, New York 1996.
3. Chebbo A.M., Irving M.R, Combined active and reactive dispatch, Proc IEE, Pt.C, (4),1995, pp. 393-405.
4. Granville S., Optimal reactive dispatch through interior point methods, IEEE Summer Meeting, Paper No. 92, SM 416-8 PWRS, 1992.
5. Contaxis G., Hatziargyriou N, Power system operation and control (in Greek), National Technical University of Athens, Department of Electrical and Computer Engineering, Electric Power Division, 2001, pp.238-243.
6. Wong K.P., Fung C.C., Simulated annealing based economic dispatch algorithm, IEE Proc. Pt.C, 1993, pp.509-515.
7. Wong K. P., Yuryevch J., Evolutionary programming-based algoritm for environnentally-constrained economic dispatch, IEEE Trans. Power Systems 13, (2), 1998,pp.301-306.
8. Mantawy A. H., Abdel-Magid Y. L., Selim S. Z., Unit commitment by tabu search, IEE Proceedings-Generation, Transmission and Distribution, 145, (1), 1998, pp.55-64.
9. Stutzle T., and Hoos H.H, Max-Min Ant System, Future Generation Computer Systems, 16, 2001, pp.889-914.
10. Bonabenn E, Dorigo M., Theraulaz G., Swarm Intelligence from natural to Artificial systems, Sante Fe Institute studies in the Sciences of complexity, Oxford University Press, 1999.
11. Dorigo M., Di Caro G., The Ant Colony Optimization Meta-Heuristic, In D.Come, M.Dorigo, and F.Glover, editors, New Ideas in optimization, Mc Graw-Hill, 1999.
12. Stutzle T., Hoos H., H., The MAX-MIN Ant System and local search for the traveling Salesman Problem, In T.Balck, Z. Michalewicz and X.Yao, editors, Proceedings of the IEEE International conference on Evolutionary Computaion, ICEC '97, 1997, pp.309-314.
13. Stutzle T., An Ant Approach to the Flow Shop Problem, Proceedings of the 6th European Congress on Intelligent Techniques and soft Computing (EUFIT '98), (3), Verlag Mainz, Aachem, 1997, pp. 1560-1564.
14. Dorigo M., Gambardella L.M, Ant Algorithms for Discrete Optimization, Artificial Life, volume 5, no.2, 1992, pp.137-172.
15. Dorigo M., Maniezzo V., and Colorni, The ant system: optimization by a colony of cooperating agents, IEE Transactions on Systems, Man, and Cybernetics, Part B, Cybernetics, 26(1), 1996, pp. 29-44.
16. Stutzle T and Hoos H.H, MAX-MIN Ant System, Future Generation Computer Systems, (16), 2000, pp.889-914.