Hybridization of Stochastic Tunneling with (Quasi)-Infinite Time-Horizon Tabu Search
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Stochastic Tunneling (STUN) is an optimization heuristic whose basic mechanism is based on reducing barriers for its search process between local optima via a non-linear transformation. Here, we hybridize STUN with the idea of Tabu Search (TS), namely, the avoidance of revisiting previously assessed solutions. This prevents STUN from inefficiently scan areas of the search space whose objective function values have already been “transformed away”. We introduce the novel idea of using a probabilistic data structure (Bloom filters) to store a (quasi-)infinite tabu history. Empirical results for a combinatorial optimization problem show superior performance. An analysis of the tabu list statistics shows the importance of this hybridization idea.
- 8.Hamacher, K.: A new hybrid metaheuristic – combining stochastic tunneling and energy landscape paving. In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds.) HM 2013. LNCS, vol. 7919, pp. 107–117. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38516-2_9CrossRefGoogle Scholar