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Hybridization of Stochastic Tunneling with (Quasi)-Infinite Time-Horizon Tabu Search

  • Kay HamacherEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11299)

Abstract

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.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science, Department of Physics and Department of BiologyTechnical University DarmstadtDarmstadtGermany

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