- Easy distributions for combinatorial optimization problems with probabilistic constraints Bernard Fortz (bfortzulb.ac.be) Michael Poss (mpossulb.ac.be) Abstract: We show how we can linearize probabilistic linear constraints with binary variables when all coefficients are distributed according to either $\mathcal{N}(\mu_i,\lambda \mu_i)$, for some $\lambda >0$ and $\mu_i>0$, or $\Gamma(k_i,\theta)$ for some $\theta >0$ and $k_i>0$. The constraint can also be linearized when the coefficients are independent and identically distributed if they are, besides, either positive or strictly stable random variables. Keywords: probabilistic constraint, combinatorial optimization, continuous distributions Category 1: Stochastic Programming Category 2: Combinatorial Optimization Citation: Download: [PDF]Entry Submitted: 10/22/2009Entry Accepted: 10/22/2009Entry Last Modified: 02/22/2010Modify/Update this entry Visitors Authors More about us Links Subscribe, Unsubscribe Digest Archive Search, Browse the Repository Submit Update Policies Coordinator's Board Classification Scheme Credits Give us feedback Optimization Journals, Sites, Societies Optimization Online is supported by the Mathematical Programming Society.