Optimization with Marginals and Moments discusses problems at the interface of optimization and probability. Combining optimization and probability leads to computational challenges. At the same time, it allows us to model a large class of planning problems. Computing the expectation of the optimal objective value for an optimization problem with random terms in it, is at the core of this.

The book explores the computation of bounds on the expected optima value where some of the terms in the optimization problems are random. Only limited information on the probability distribution of the random variables is assumed to be known.

The book explores models and methods using which tight and efficiently computable bounds can be derived. it brings together ideas that have at times originated in different research communities, some older and some newer ideas, all viewed through the lends of computing bounds in optimization with marginals and moments. Applications and exercises are provided to aid the reader in obtaining greater mastery over the subject.