Abstract The most important ingredient for solving mixed-integer nonlinear programs (MINLPs) to global $$\epsilon $$ ϵ -optimality with spatial branch and bound is a tight, computationally tractable relaxation. Due both theoretical practical considerations, relaxations of MINLPs are usually required be convex...

We present a generic branch-and-bound algorithm for finding all the Pareto solutions of biobjective mixed-integer linear program. The main contributions are new algorithms obtaining dual bounds at node, checking node fathoming, presolve, and duality gap measurement. Our is predominantly decision space search method because branching performed on variables, akin to single objective problems, alt...

In this article, we consider a network of processors aiming at cooperatively solving mixed-integer convex programs subject to uncertainty. Each node only knows common cost function and its local uncertain constraint set. We propose randomized, distributed algorithm working under asynchronous, unreliable, directed communication. The is based on computation communication paradigm. At each round, ...