Examinando por Autor "Escudero, Laureano F"

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An approach for Strategic Supply Chain Planning under Uncertainty based on Stochastic 0-1 Programming
(Springer Verlag, 2003) Alonso-Ayuso, Antonio; Escudero, Laureano F; Garín, Araceli; Ortuño, M Teresa; Pérez, Gloria
We present a two-stage stochastic 0-1 modeling and a related algorithmic approach for Supply Chain Management under uncertainty, whose goal consists of determining the production topology, plant sizing, product selection, product allocation among plants and vendor selection for raw materials. The objective is the maximization of the expected benefit given by the product net profit over the time horizon minus the investment depreciation and operations costs. The main uncertain parameters are the product net price and demand, the raw material supply cost and the production cost. The first stage is included by the strategic decisions. The second stage is included by the tactical decisions. A tight 0-1 model for the deterministic version is presented. A splitting variable mathematical representation via scenario is presented for the stochastic version of the model. A two-stage version of a Branch and Fix Coordination (BFC) algorithmic approach is proposed for stochastic 0-1 program solving, and some computational experience is reported for cases with dozens of thousands of constraints and continuous variables and hundreds of 0-1 variables.
BFC, A Branch-and-Fix Coordination Algorithmic Framework for solving Some Types of Stochastic Pure and Mixed 0-1 Programs
(Elsevier, 2003) Alonso-Ayuso, Antonio; Escudero, Laureano F; Ortuño, M Teresa
We present a framework for solving some types of $0-1$ multi-stage scheduling/planning problems under uncertainty in the objective function coefficients and the right-hand-side. A scenario analysis scheme with full recourse is used. The solution offered for each scenario group at each stage takes into account all scenarios but without subordinating to any of them. The constraints are modelled by a splitting variables representation via scenarios. So, a $0-1$ model for each scenario is considered plus the non-anticipativity constraints that equate the $0-1$ variables from the same group of scenarios in each stage. The mathematical representation of the model is very amenable for the proposed framework to deal with the $0-1$ character of the variables. A Branch-and-Fix Coordination approach is introduced for coordinating the selection of the branching nodes and branching variables in the scenario subproblems to be jointly optimized. Some computational experience is reported for different types of problems.
Collision Avoidance in the ATM Problem: A Mixed Integer Linear Optimization Approach
(IEEE, 2011) Alonso-Ayuso, Antonio; Escudero, Laureano F; Martín-Campo, F Javier
This paper tackles the collision avoidance problem in ATM. The problem consists in deciding the best strategy for new aircraft configurations (velocity and altitude changes) such that all conflicts in the airspace are avoided; a conflict being the loss of the minimum safety distance that has to be kept between two aircrafts. A mixed 0-1 linear optimization model based on geometric transformations for collision avoidance between an arbitrary number of aircrafts in the airspace is developed. Knowing initial coordinates, angle direction and level flight, the new configuration for each aircraft is established by minimizing several objectives like velocity variation and total number of changes (velocity and altitude), and forcing to return to the original flight configuration when no aircrafts are in conflict. Due to the small computational time for the execution, the new configuration approach can be used in real time by using optimization software.
Conflict Avoidance: 0-1 linear models for Conflict Detection & Resolution
(Springer, 2013) Alonso-Ayuso, Antonio; Escudero, Laureano F; Olaso, Pablo; Pizarro, Celeste
The Conflict Detection and Resolution Problem for Air Traffic Flow Man- agement consists of deciding the best strategy for airborne aircraft so that there is guarantee that no conflict takes place, i.e., all aircraft maintain the minimum safety distance at every time instant. Two integer linear optimization models for conflict avoidance between any number of aircraft in the airspace are proposed, the first being a pure 0-1 linear which avoids conflicts by means of altitude changes, and the second a mixed 0-1 linear whose strategy is based on altitude and speed changes. Several ob- jective functions are established. Due to the small elapsed time that is required for solving both problems, the approach can be used in real time by using state-of-the-art mixed integer linear optimization software.
Lagrangean decomposition for large-scale two-stage stochastic mixed 0-1 problems
(Universidad Rey Juan Carlos, 2010) Escudero, Laureano F; Garín, Araceli; Pérez, Gloria; Unzueta, A
Medium range optimization of copper extraction planning under uncertainty in future copper prices
(2011-11-24) Alonso-Ayuso, Antonio; Carvallo, Felipe; Escudero, Laureano F; Guignard, Monique; Pi, Jiaxing; Purammalka, Raghav; Weintraub, Andres
Deterministic mine planning models along a time horizon have proved to be very effective in supporting decisions on sequencing the extraction of material in copper mines. Some of these models have been developed for, and used successfully by CODELCO, the Chilean state copper company. These models are extremely large. In this paper, we wish to consider the uncertainty in a very volatile parameter of the problem, namely, the copper price along a given time horizon. We represent the uncertainty by a multistage scenario tree. The resulting stochastic model is then converted into a mixed 0-1 Deterministic Equivalent Model using a compact representation. We first introduce the stochastic model that maximizes the expected profit along the time horizon over all scenarios (i.e., as in a risk neutral environment). We then present several approaches for risk management, in a risk averse environment. Specifically, we consider the maximization of the Value-at-Risk and several variants of the Conditional Value-at-Risk, the maximization of the expected profit minus the weighted probability of having a ``bad" scenario in the solution provided by the model, and the maximization of the expected profit subject to stochastic dominance constraints for a set of profiles given by the pairs of target profits and bounds on either the probability of not reaching them or the expected profit deficit over the targets. We present an extensive computational experience on the actual problem, by comparing the risk neutral approach, the tested risk averse strategies and the performance of the traditional deterministic approach that uses the expected value of the uncertain parameters. The results clearly show the advantage of using any risk neutral strategy over the traditional deterministic approach, as well as the advantage of using the risk averse strategy over the risk neutral one, although the plain use of the MIP solvers should be replaced by decomposition algorithms.
On modeling the air traffic control coordination in the collision avoidance problem by mixed integer linear optimization
(Springer, 2014-09) Alonso-Ayuso, Antonio; Escudero, Laureano F; Martín-Campo, Francisco Javier
On the Product Selection and Plant Dimensioning Problem under uncertainty
(Elsevier, 2005) Alonso-Ayuso, Antonio; Escudero, Laureano F; Garín, Araceli; Ortuño, M Teresa; Pérez, Gloria
We present a two-stage full recourse model for strategic production planning under uncertainty, whose aim consists of determining product selection and plant dimensioning. The main uncertain parameters are the product price, demand and production cost. The benefit is given by the product net profit over the time horizon minus the investment depreciation and operation costs. The Value-at-Risk and the reaching probability are considered as risk measures in the objective function to be optimized as alternatives to the maximization of the expected benefit over the scenarios. The uncertainty is represented by a set of scenarios. The problem is formulated as a mixed 0--1 Deterministic Equivalent Model. The strategic decisions to be made in the first stage are represented by 0--1 variables. The tactical decisions to be made in the second stage are represented by continuous variables. An approach for problem solving based on a splitting variable mathematical representation via scenario is considered. The problem uses the Twin Node Family concept within the algorithmic framework known as Branch-and-Fix Coordination for satisfying the nonanticipativity constraints. Some computational experience is reported.
Stochastic Set PStochastic Set Packing Problemacking Problem
(Universidad Rey Juan Carlos, 2010) Escudero, Laureano F; Landete, Mercedes; Rodríguez-Chía, Antonio M
Structuring bilateral energy contract portfolios in competitive markets
(2010) Alonso-Ayuso, Antonio; Domenica, Nico di; Escudero, Laureano F; Pizarro, Celeste