Abstract
This paper proposes a Binary Ant Colony Optimization applied to constrained optimization problems with binary solution structure. Due to its simple structure, the convergence status of the proposed algorithm can be monitored through the distribution of pheromone in the solution space, and the probability of solution improvement can be in some way controlled by the maintenance of pheromone. The successful implementations to the binary function optimization problem and the multidimensional knapsack problem indicate the robustness and practicability of the proposed algorithm.
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References
Dorigo, M., Maniezzo, V., Colorni, A.: Positive feedback as a search strategy. Technical report, Dipartimento di Elettronica e Informatica, Politecnico di Milano, IT (1991)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics, Part B 26(1), 29–41 (1996)
Gambardella, L., Taillard, E., Agazzi, G.: Macs-vrptw: a multiple ant colony system for vehicle routing problems with time windows. In: Corne, D., Dorgo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 63–76. McGraw-Hill Ltd., New York (1999)
Gambardella, L., Taillard, E., Dorigo, M.: Ant colonies for the quadratic assignment problem. Journal of the Operational Research Society 50(2), 167–176 (1999)
Gutjahr, W.: A graph-based ant system and its convergence. Future Generation Computer Systems 16(8), 873–888 (2000)
Stützle, T., Dorigo, M.: A short convergence proof for a class of ant colony optimization algorithms. IEEE Transactions on Evolutionary Computation 6(4), 358–365 (2002)
Kong, M., Tian, P.: A convergence proof for the ant colony optimization algorithms. In: 2005 International Conference on Artificial Intelligence, ICAI 2005, pp. 27–30 (2005)
Blum, C., Dorigo, M.: The hyper-cube framework for ant colony optimization. IEEE Transactions on Systems, Man and Cybernetics, Part B 34(2), 1161–1172 (2004)
Baluja, S., Caruana, R.: Removing the genetics from the standard genetic algorithm. In: Prieditis, A., Russel, S. (eds.) The International Conference on Machine Learning 1995, pp. 38–46. Morgan-Kaufmann Publishers, San Francisco (1995)
Bilchev, G., Parmee, I.: Constrained optimization with an ant colony search model. In: 2nd International Conference on Adaptive Computing in Engineering Design and Control, pp. 26–28 (1996)
Monmarche, N., Venturini, G., Slimane, M.: On how pachycondyla apicalis ants suggest a new search algorithm. Future Generation Computer Systems 16(8), 937–946 (2000)
Dreo, J., Siarry, P.: Continuous interacting ant colony algorithm based on dense heterarchy. Future Generation Computer Systems 20(5), 841–856 (2004)
Socha, K.: ACO for continuous and mixed-variable optimization. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 25–36. Springer, Heidelberg (2004)
Chu, P., Beasley, J.: A genetic algorithm for the multidimentional knapsack problem. Journal of Heuristics 4(1), 63–86 (1998)
Leguizamon, G., Michalewicz, Z.: A new version of ant system for subset problems. In: Congress on Evolutionary Computation, pp. 1459–1464 (1999)
Fidanova, S.: Evolutionary algorithm for multidimensional knapsack problem. In: The Seventh International Conference on Parallel Problem Solving from Nature (PPSNVII) Workshop (2002)
Alaya, I., Solnon, C., Ghedira, K.: Ant algorithm for the multi-dimensional knapsack problem. In: International Conference on Bioinspired Optimization Methods and their Applications (BIOMA 2004), pp. 63–72 (2004)
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Kong, M., Tian, P. (2006). Introducing a Binary Ant Colony Optimization. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_44
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DOI: https://doi.org/10.1007/11839088_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38482-3
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