An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling
نویسنده
چکیده
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 problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems.
منابع مشابه
Medium Term Hydroelectric Production Planning - A Multistage Stochastic Optimization Model
Multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. One of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...
متن کاملInexact Cuts in Benders Decomposition
Benders' decomposition is a well-known technique for solving large linear programs with a special structure. In particular it is a popular technique for solving multi-stage stochastic linear programming problems. Early termination in the subproblems generated during Benders' decomposition (assuming dual feasibility) produces valid cuts which are inexact in the sense that they are not as constra...
متن کاملOn regularization with normal solutions in decomposition methods for multistage stochastic programming
We consider well-known decomposition techniques for multistage stochastic programming and a new scheme based on normal solutions for stabilizing calculations as the iteration process progresses. The given algorithms combine ideas from finite perturbation of convex programs and level bundle methods to regularize the so-called forward step of these decomposition methods. In contrast to other regu...
متن کاملiii OPTIMAL INFRASTRUCTURE MAINTENANCE SCHEDULING PROBLEM UNDER BUDGET UNCERTAINTY
This research addresses a general class of infrastructure asset management problems. Infrastructure agencies usually face budget uncertainties that will eventually lead to suboptimal planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance scheduling policies that take future budget uncertainty into co...
متن کاملA stochastic model for project selection and scheduling problem
Resource limitation in zero time may cause to some profitable projects not to be selected in project selection problem, thus simultaneous project portfolio selection and scheduling problem has received significant attention. In this study, budget, investment costs and earnings are considered to be stochastic. The objectives are maximizing net present values of selected projects and minimizing v...
متن کامل