A new solution algorithm for improving performance of ant colony optimization

Applied Mathematics and Computation

Volumn 211, Issue 1, 2009, Pages 75-84

  Baskan, Ozgur ^a   Haldenbilen, Soner ^a   Ceylan, Huseyin ^a   Ceylan, Halim ^a  

^a PAMUKKALE UNIVERSITY   (Turkey)

Author keywords

Ant colony optimization; Function minimization; Meta heuristics; Reduced search space

Indexed keywords

ACO ALGORITHMS; ANT COLONIES; ANT COLONY OPTIMIZATION; ARTIFICIAL INTELLIGENT; DECISION-MAKING PROCESS; GLOBAL OPTIMUM; IMPROVING PERFORMANCE; MATHEMATICAL FUNCTIONS; META-HEURISTICS; MINIMUM VALUES; NEW SOLUTIONS; NUMBER OF ITERATIONS; OBJECTIVE FUNCTIONS; OPTIMIZATION ALGORITHMS; OPTIMIZATION METHODS; REDUCED SEARCH SPACE; SOLUTION ALGORITHMS; TEST FUNCTIONS;

ALGORITHMS; CONSTRAINED OPTIMIZATION; FUNCTIONS; HEURISTIC METHODS; SIMULATED ANNEALING; TABU SEARCH; THREE TERM CONTROL SYSTEMS;

FUNCTION EVALUATION;

EID: 64049119705     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2009.01.025     Document Type: Article

References (24)

1. Toksari{dotless} M.D. Ant colony optimization for finding the global minimum. Applied Mathematics and Computation 176 (2006) 308-316
2. Toksari{dotless} M.D. A heuristic approach to find the global optimum of function. Journal of Computational and Applied Mathematics 209 2 (2007) 160-166
3. Hamzacebi C., and Kutay F. A heuristic approach for finding the global minimum: adaptive random search technique. Applied Mathematics and Computation 173 2 (2006) 1323-1333
4. Li J., and Rhinehart R.R. Heuristic random optimization. Computers and Chemical Engineering 22 3 (1998) 427-444
5. Hamzacebi C. Improving genetic algorithms' performance by local search for continuous function optimization. Applied Mathematics and Computation 196 (2008) 309-317
6. Hamzacebi C. Continuous functions minimization by dynamic random search technique. Applied Mathematical Modelling 31 (2007) 2189-2198
7. Kwon Y.D., Kwon S.B., and Kim J. Convergence enhanced genetic algorithm with successive zooming method for solving continuous optimization problems. Computers and structures 81 (2003) 1715-1725
8. M. Dorigo, G. Di Caro, Ant colony optimisation: a new meta-heuristic, in: Proceedings of the 1999 Congress on Evolutionary Computation, vol. 2, 1999, pp. 1470-1477.
9. Donati A.V., Montemanni R., Casagrande N., Rizzoli A.E., and Gambardella L.M. Time dependent vehicle routing problem with a multi ant colony system. European Journal of Operational Research 185 3 (2008) 1174-1191
10. Bell J.E., and McMullen P.R. Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics 18 (2004) 41-48
11. Talbi E.G., Roux O., Fonlupt C., and Robillard D. Parallel ant colonies for the quadratic assignment problem. Future Generation Computer Systems 17 (2001) 441-449
12. Demirel N.C., and Toksari M.D. Optimization of the quadratic assignment problem using an ant colony algorithm. Applied Mathematics and Computation 183 (2006) 427-435
13. Dreo J., and Siarry P. An ant colony algorithm aimed at dynamic continuous optimization. Applied Mathematics and Computation 181 (2006) 457-467
14. Kuan S.N., Ong H.L., and Ng K.M. Solving the feeder bus network design problem by genetic algorithms ad ant colony optimization. Advances in Engineering Software 37 (2006) 351-359
15. Poorzahedy H., and Abulghasemi F. Application of Ant system to network design problem. Transportation 32 (2005) 251-273
16. Wang H., and Shen J. Heuristic approaches for solving transit vehicle scheduling problem with route and fueling time constraints. Applied Mathematics and Computation 190 (2007) 1237-1249
17. Cheng C.B., and Mao C.P. A modified ant colony system for solving the travelling salesman problem with time windows. Mathematical and Computer Modelling 46 (2007) 1225-1235
18. Schwefel H.P. Numerical Optimization of Computer Models (1981), Wiley & Sons, Chichester
19. M. Dorigo, T. Stützle, Ant Colony Optimization, MIT Press, Massachusetts Institute of Technology, Cambridge, 2004.
20. M. Dorigo, Optimization, learning and natural algorithms, Ph.D. Thesis, Politecnico di Milano, Italy, 1992.
21. Denebourg J.L., Pasteels J.M., and Verhaeghe J.C. Probabilistic behaviour in ants: a strategy of errors?. Journal of Theoretical Biology 10 (1983) 259-271
22. Shelokar P.S., Siarry P., Jayaraman V.K., and Kulkarni B.D. Particle swarm and ant colony algorithms hybridized for improved continuous optimization. Applied Mathematics and Computation 188 (2007) 129-142
23. Toksari M.D. Minimizing the multimodal functions with ant colony optimization approach. Expert Systems with Applications 36 (2009) 6030-6035
24. Chelouah R., and Siarry P. Tabu Search applied to global optimization. European Journal of Operational Research 123 (2000) 256-270