Fitting Distributions with the Polyhazard Model with Dependence

The polyhazard model with dependent causes, first introduced to fit lifetime data, generalized the traditional polyhazard model by allowing the latent causes of failure to be dependent by using copula functions. When modeling lifetime data, marginal distributions are supported on the positive reals. Dropping this restriction, the method generates a rich family of univariate distributions with asymmetries and multiple modes. We show that this new family of distributions is able to approximate other distributions proposed in the literature, such as the generalized beta-generated distributions. These distributions are fitted to three real data sets.     

Pattern-based ILP models for the one-dimensional cutting stock problem with setup cost

Journal of Combinatorial Optimization - The one-dimensional cutting stock problem with setup cost (CSP-S) is a cutting problem that seeks a cutting plan with a minimum number of objects and a...