Now SLS behavior on COP Fitness Landscape is no longer too mysterious!


Steven Halim
Roland Yap
Lau Hoong Chuin
Felix Halim


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Latest Updates

9 Jun 2010: After almost two years of hibernation, we are back... This URL will be the main website for Viz from now onwards. Viz v3 will be released soon.

5 Sep 2008: Viz v3 in testing phase! Click here to see the sneak preview!

Viz is an off-line, user-friendly, GUI-based, Stochastic Local Search (SLS) engineering suite (version history).

Viz can be used to visually analyze (white-box) Stochastic Local Search (SLS) (sometimes also referred as metaheuristic) algorithms while they are traversing the fitness landscapes of NP-hard Combinatorial Optimization Problems (COPs). This visualization is generic, which means that it can virtually be used to visually analyze almost any COPs that is attacked by an SLS algorithm. The visualization visualize both the fitness landscape (FL) of a COP instance and the search trajectory (ST) of a heuristic and stochastic SLS algorithm on that fitness landscape (the basic ideas behind this FLST visualization are explained here). Understanding search trajectory behavior of our SLS algorithm on the COP instances being attacked empowers the user (algorithm designer) to design better performing algorithm and focus the parameter space to a much smaller one. Once the SLS algorithm has been (carefully) designed and parameter space is (significantly) focused, Viz can then be instructed to perform full-factorial design (black-box) on the focused configuration space for even better performing algorithm.

We know that to engineer good performing SLS, one needs to design, implement, tune, analyze the SLS algorithm. The visualization in Viz is as a good tool for the design and analysis parts. The full-factorial design capability in Viz is a good tool for the tuning part. This combination is referred as the Integrated White+Black Box Approach.

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