As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
We propose two random generation models for MaxSAT and Partial MaxSAT in order to produce instances more similar to the industrial benchmarks used in the MaxSAT evaluation. Following the work of [4] and [2], we analyze properties of industrial instances and use a non-uniform (powerlaw) distribution to select the variables.
We also study empirically the optimum (minim number of unsatisfiable clauses) that we obtain with these models, and the relative performance of some MaxSAT solvers. We observe that industrial specialized MaxSAT solvers are better on these random formulas than random specialized solvers. We conclude that instances generated with these new models are more similar to industrial instances than the generated with the classical random models based on uniform probability distributions.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.