Modeling uncertainty processes for multi-stage optimization of strategic energy planning: An auto-regressive and Markov chain formulation

Categories Applications - OR and Management Sciences, Stochastic Programming Tags , , ,

This paper deals with the modeling of stochastic processes in long-term multistage energy planning problems when little information is available on the degree of uncertainty of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through autoregressive (AR) … Read more

Intraday Power Trading: Towards an Arms Race in Weather Forecasting?

Categories Finance and Economics, Stochastic Programming Tags , , , ,

We propose the first weather-based algorithmic trading strategy on a continuous intraday power market. The strategy uses neither production assets nor power demand and generates profits purely based on superior information about aggregate output of weather-dependent renewable production. We use an optimized parametric policy based on state-of-the-art intraday updates of renewable production forecasts and evaluate … Read more

Exact Solutions to a Carsharing Pricing and Relocation Problem under Uncertainty

Categories Stochastic Programming, Transportation Tags , ,

In this article we study the problem of jointly deciding carsharing prices and vehicle relocations. We consider carsharing services operating in the context of multi-modal urban transportation systems. Pricing decisions take into account the availability of alternative transport modes, and customer preferences with respect to these. In order to account for the inherent uncertainty in … Read more

Non-anticipative risk-averse analysis with effective scenarios applied to long-term hydrothermal scheduling

Categories Nonlinear Optimization, Stochastic Programming Tags , , ,

In this paper, we deal with long-term operation planning problems of hydrothermal power systems by considering scenario analysis and risk aversion. This is a stochastic sequential decision problem whose solution must be non-anticipative, in the sense that a decision at a stage cannot use a perfect knowledge of the future. We propose strategies to reduce … Read more

An efficient solution methodology for the airport slot allocation problem with preprocessing and column generation

Categories Airline Optimization, Scheduling, Transportation Tags , , , ,

Airport coordination is a demand control mechanism that maximizes the use of existing infrastructure at congested airports. Aircraft operators submit a list of regular flights that they wish to operate over a five to seven-month period and a designated coordinator is responsible for allocating the available airport slots, which represent the permission to operate a … Read more

Randomized Policy Optimization for Optimal Stopping

Categories Dynamic Programming, Finance and Economics, Unconstrained Optimization Tags , , , , ,

Optimal stopping is the problem of determining when to stop a stochastic system in order to maximize reward, which is of practical importance in domains such as finance, operations management and healthcare. Existing methods for high-dimensional optimal stopping that are popular in practice produce deterministic linear policies — policies that deterministically stop based on the … Read more

Stochastic Gauss-Newton Algorithms for Online PCA

Categories Stochastic Programming Tags , , ,

In this paper, we propose a stochastic Gauss-Newton (SGN) algorithm to study the online principal component analysis (OPCA) problem, which is formulated by using the symmetric low-rank product (SLRP) model for dominant eigenspace calculation. Compared with existing OPCA solvers, SGN is of improved robustness with respect to the varying input data and algorithm parameters. In … Read more

A Hessian inversion-free exact second order method for distributed consensus optimization

Categories Global Optimization Tags , , , ,

We consider a standard distributed consensus optimization problem where a set of agents connected over an undirected network minimize the sum of their individual (local) strongly convex costs. Alternating Direction Method of Multipliers (ADMM) and Proximal Method of Multipliers (PMM) have been proved to be effective frameworks for design of exact distributed second order methods … Read more

An Asynchronous Proximal Bundle Method

Categories Convex and Nonsmooth Optimization Tags , , , ,

We develop a fully asynchronous proximal bundle method for solving non-smooth, convex optimization problems. The algorithm can be used as a drop-in replacement for classic bundle methods, i.e., the function must be given by a first-order oracle for computing function values and subgradients. The algorithm allows for an arbitrary number of master problem processes computing … Read more

Spectral Projected Subgradient Method for Nonsmooth Convex Optimization Problems

Categories Constrained Nonlinear Optimization, Convex and Nonsmooth Optimization, Convex Optimization Tags , , , , ,

We consider constrained optimization problems with a nonsmooth objective function in the form of mathematical expectation. The Sample Average Approximation (SAA) is used to estimate the objective function and variable sample size strategy is employed. The proposed algorithm combines an SAA subgradient with the spectral coefficient in order to provide a suitable direction which improves … Read more