A novel sequential optimality condition for smooth constrained optimization and algorithmic consequences

In the smooth constrained optimization setting, this work introduces the Domain Complementary Approximate Karush-Kuhn-Tucker (DCAKKT) condition, inspired by a sequential optimality condition recently devised for nonsmooth constrained optimization problems. It is shown that the augmented Lagrangian method can generate limit points satisfying DCAKKT, and it is proved that such a condition is not related to … Read more

Two-Stage Robust Optimization with Decision Dependent Uncertainty

The type of decision dependent uncertainties (DDUs) imposes a great challenge in decision making, while existing methodologies are not sufficient to support many real practices. In this paper, we present a systematic study to handle this challenge in two-stage robust optimization~(RO). Our main contributions include three sophisticated variants of column-and-constraint generation method to exactly compute … Read more

Operation of an ambulance fleet under uncertainty

We introduce two new optimization models for the dispatch of ambulances. These models are to our knowledge the first providing a full modelling of the operation of an ambulance fleet, taking into account all or almost all constraints of the problem. The first model, called the ambulance selection problem, is used when an emergency call … Read more

Improving the global convergence of Inexact Restoration methods for constrained optimization problems

Inexact restoration (IR) methods are an important family of numerical methods for solving constrained optimization problems, with applications to electronic structures and bilevel programming, among others areas. In these methods, the minimization is separated into two phases: decreasing infeasibility (feasibility phase) and improving solution (optimality phase). The feasibility phase does not require the generated points … Read more

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

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?

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

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

Formulations of the max k-cut problem on classical and quantum computers

Recent claims on “solving” combinatorial optimization problems via quantum computers have attracted researchers to work on quantum algorithms. The max k-cut problem is a challenging combinatorial optimization problem with multiple notorious mixed integer linear optimization formulations. In this paper, we revisit the binary quadratic optimization formulation of Carlson and Nemhauser (Operations Research, 1966) and provide … Read more

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

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

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