An Integrated White+Black Box Approach for Designing and Tuning Stochastic Local Search

Abstract. Stochastic Local Search (SLS) is a simple and effective paradigm for attacking a variety of Combinatorial (Optimization) Problems (COP). However, it is often non-trivial to get good results from an SLS; the designer of an SLS needs to undertake a laborious and ad-hoc algorithm tuning and re-design process for a particular COP. There are two general approaches. Black-box approach treats the SLS as a black-box in tuning the SLS parameters. White-box approach takes advantage of humans to observe the SLS in the tuning and SLS re-design. In this paper, we develop an integrated white+black box approach with extensive use of visualization (white-box) and factorial design (black-box) for tuning, and more importantly, for designing arbitrary SLS algorithms. Our integrated approach combines the strengths of white-box and black-box approaches and produces better results than either alone. We demonstrate an effective tool using the integrated white+black box approach to design and tune...

• Type: Conference
• Year: 2007
• Where: CP
• Authors: Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
• Keywords: Black-box, CP 2007, Programming Languages, SLS Re-design, White+black Box Approach