Do not be afraid of local minima: affine shaker and particle swarm

Battiti, Roberto and Brunato, Mauro and Pasupuleti, Srinivas (2005) Do not be afraid of local minima: affine shaker and particle swarm. UNSPECIFIED. (Unpublished)

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    Stochastic local search techniques are powerful and flexible methods to optimize difficult functions. While each method is characterized by search trajectories produced through a randomized selection of the next step, a notable difference is caused by the interaction of different searchers, as exemplified by the Particle Swarm methods. In this paper we evaluate two extreme approaches, Particle Swarm Optimization, with interaction between the individual "cognitive" component and the "social" knowledge, and Repeated Affine Shaker, without any interaction between searchers but with an aggressive capability of scouting out local minima. The results, unexpected to the authors, show that Affine Shaker provides remarkably efficient and effective results when compared with PSO, while the advantage of Particle Swarm is visible only for functions with a very regular structure of the local minima leading to the global optimum and only for specific experimental conditions.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: Q Science > QA Mathematics > QA063 Problem solving
    Uncontrolled Keywords: Local Search, Particle Swarm, Affine Shaker
    Report Number: DIT-05-049
    Repository staff approval on: 23 Jun 2005

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