Abstract
In this paper, we describe user interaction with an optimization algorithm via a sophisticated visualization interface that we created for this purpose. Our primary interest is the tool itself. We demonstrate that a user wielding this tool can find ways to improve the performance of an ant colony optimization (ACO) algorithm as applied to a problem of finding 3D paths in the presence of impediments [14]. One part of a solution method can be to find a path on a grid. Of course, there are near linear time algorithms for the shortest path that have been applied to problems that are quite large. However, for a grid in three dimensions with arcs on the axes and diagonals, the problems can become extremely large as resolution is increased and heuristics thus make sense (see, e.g., [6] for state-of-the art algorithms where pre-processing is possible). Ant colony optimization (see, e.g., [4,5]) is ideally suited to such a problem.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brunner, J.D., Jablonowski, D.J., Bliss, B., Haber, R.B.: Vase: the visualization and application steering environment. In: Supercomputing 1993. Proceedings of the 1993 ACM/IEEE conference on Supercomputing, pp. 560–569. ACM Press, New York (1993)
Bullnheimer, B., Hartl, R., Strauss, C.: A new rank based version of the ant system. Central European Journal for Operations Research and Economics 7, 25–38 (1999)
Card, S.K., Mackinlay, J.D., Shneiderman, B. (eds.): Readings in information visualization: using vision to think. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1999)
Dorigo, M., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5, 137–172 (1999)
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, 1–13 (1997)
Goldberg, A.V., Kaplan, H., Werneck, R.: Reach for A*: Efficient point-to-point shortest path algorithms, http://research.microsoft.com/research/pubs/view.aspx?type=Technical%20Report&id=986
Hammond, S.P.: Putting the user in the loop: On-line user adaption of genetic algorithms. In: Sarker, R., Reynolds, R., Abbass, H., Chen Tan, K., McKay, B., Essam, D., Gedeon, T. (eds.) Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, pp. 892–897. IEEE Press, Los Alamitos (2003)
Klau, G.W., Lesh, N.B., Marks, J.W., Mitzenmacher, M.: Human-guided tabu search. In: National Conference on Artificial Intelligence (AAAI), pp. 41–47 (2002)
Kreylos, O., Tesdall, A.M., Hamann, B., Hunter, J.K., Joy, K.I.: Interactive visualization and steering of CFD simulations. In: VISSYM 2002: Proceedings of the Symposium on Data Visualisation 2002, Aire-la-Ville, Switzerland, pp. 25–34. Eurographics Association (2002)
Lesh, N., Lopes, L.B., Marks, J., Mitzenmacher, M., Schafer, G.T.: Human-guided search for jobshop scheduling. In: 3rd International NASA Workshop on Planning and Scheduling for Space (October 2002)
Mulder, J.D., van Wijk, J.J., van Liere, R.: A survey of computational steering environments. Future Gener. Comput. Syst. 15(1), 119–129 (1999)
Nakamichi, Y., Arita, T.: Diversity control in ant colony optimization. Artificial Life and Robotics 7, 1614–7456 (2004)
Stützle, T., Hoos, H.: \(\mathcal{MAX-MIN}\) ant system. Future Generations Computer Systems Journal, 16 (2000)
Verhoeven, M., Woodruff, D.L.: Optimizing paths in the presence of spherical impediments. Technical report, GSM, UC Davis, Davis CA, 95616 (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sreevalsan-Nair, J., Verhoeven, M., Woodruff, D.L., Hotz, I., Hamann, B. (2007). Human-Guided Enhancement of a Stochastic Local Search: Visualization and Adjustment of 3D Pheromone. In: Stützle, T., Birattari, M., H. Hoos, H. (eds) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. SLS 2007. Lecture Notes in Computer Science, vol 4638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74446-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-74446-7_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74445-0
Online ISBN: 978-3-540-74446-7
eBook Packages: Computer ScienceComputer Science (R0)