Cutting plane methods play a significant role in modern solvers for tackling mixed-integer programming (MIP) problems. Proper selection of cuts would remove infeasible solutions the early stage, thus largely reducing computational burden without hurting solution accuracy. However, major cut approaches heavily rely on heuristics, which strongly depend specific problem at hand and limit their gen...

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, ...