Online resource allocation problems are difficult because the operator must make irrevocable decisions rapidly and with limited (or nonexistent) information on future requests. We propose a mathematical-programming-based framework that takes into account all the available forecasts and the limited computational time. We combine Benders decomposition, which allows us to measure the expected futu...

Direct current (DC) electricity distribution systems have been proposed as an alternative to traditional, alternating current (AC) distribution systems for commercial buildings. Partial replacement of AC distribution with DC distribution can improve service to DC loads and overall building energy efficiency. This article develops (i) a mixed-integer, nonlinear, nonconvex mathematical programmin...

Robust optimization extends stochastic programming models by incorporating measures of variability into the objective function. This paper explores robust optimization in the context of two-stage planning systems. First, we propose the use of a generalized Benders decomposition algorithm for solving robust models. Next, we argue that using an arbitrary measure for variability can lead to sub-op...

This paper presents a decomposition approach for linear multistage stochastic programs, that is based on the concept of recombining scenario trees. The latter, widely applied in Mathematical Finance, may prevent the node number of the scenario tree to grow exponentially with the number of time stages. It is shown how this property may be exploited within a non-Markovian framework and under time...

With the growing adoption of renewable energy resources in power grid, co-optimizing operation water and distribution networks (WDNs PDNs) increases flexibility both systems. The optimal flow problem (OWPF) is formulated to manage resource utilization across WDNs multi-phase PDNs. nonlinear WDN hydraulic constraints PDN ac equations render OWPF nonconvex. This paper formulates a convex (C-OWPF)...

Supply chain transportation operations often account for a large proportion of product total cost to market. Such can be optimized by solving the Logistics Service Network Design Problem (LSNDP), wherein logistics service provider seeks cost-effectively source and fulfill customer demands products within multi-echelon distribution network. However, many industrial settings yield instances LSNDP...

This paper presents an optimization model and its application to a generation expansion planning problem. The proposed model has a generalized network structure and is exploited effectively by Benders’ decomposition algorithm, where a master problem generates trial expansion plans and a set of subproblems compute production cost and system reliability for the trial plan. The applicability of ou...

Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such probl...