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, ...

Abstract The analysis of infeasible subproblems plays an important role in solving mixed integer programs (MIPs) and is implemented most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from subproblems: conflict graph dual proof analysis. While detects sets contradicting variable bounds implication graph, derives linear the LP’s unboundedne...

multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. the optimality of such optimizations is largely defined through the pareto optimality. multiple objective integer linear programs (moilp) are special cases of multiple criteria decision making problems. numerous algorithms have been desig...