A parallel computation approach for solvingmultistage stochastic network problems

This paper presents a parallel computation approach for the efficient solution of verylarge multistage linear and nonlinear network problems with random parameters. Theseproblems result from particular instances of models for the robust optimization of networkproblems with uncertainty in the values of the right‐hand side and the objective functioncoefficients. The methodology considered here models the uncertainty using scenarios tocharacterize the random parameters. A scenario tree is generated and, through the use offull‐recourse techniques, an implementable solution is obtained for each group of scenariosat each stage along the planning horizon.