Artículos de Revista

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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.
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.
On a selection and scheduling problem in automatic storage and retrieval warehouses
(Taylor and Francis, 2013) Alonso-Ayuso, Antonio; Tirado, Gregorio; Udías, Ángel
Warehousing is one of the main components of the supply chain and its optimization is crucial to achieve global efficiency. Warehouse operations in- volve receiving, shipping, storing and order picking, among others, and the coordinated optimization of all these different operations is highly complex. This paper approaches a selection and scheduling real problem that arises in an automatic storage/retrieval warehouse system involving the scheduling of forklifts pickup operations. The objective is to minimize the total loading time of the vehicles performing transportation, while respecting their departure due dates. This complex problem is approached through a two-phase decomposi- tion method, combining both exact and heuristic procedures. The performance of the proposed solution method is evaluated through extensive computational results performed on several scenarios from a real case study built from data from a real mattress warehouse.
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.
The radar method: An effective line search for piecewise linear concave functions
(Springer Verlag, 2009) Beltrán-Royo, César
Two alternative models for farm management: discrete versus continuous time horizo
(Elsevier, 2003) Vitoriano, Begoña; Ortuño, M Teresa; Recio, Beatriz; Rubio, Fernando; Alonso-Ayuso, Antonio
Crop production entails many decision making processes aimed at improving productivity and achieving the best yield from scarce resources. Assuming that there is a set of tasks to be carried out within a given time horizon, and each task can be performed in different ways, the problem consists of determining how and when to carry out each task, in such a way that the tasks are scheduled in sequence at the minimum cost, taking into account any precedence relationships among them, the time window constraints for performing the tasks and the resources availability. This paper presents two alternative mathematical models to attain the proposed objective. The first model splits the time into discrete units spread throughout the planning horizon; it is presented in connection with flexible manufacturing. The second model keeps a continuous time horizon; a scheduling model is used for which a family of {\it incompatibility conditions} is introduced to avoid a certain type of simultaneous usage of resources. This type of conditions require to introduce a new structure so-called conditional disjunction. Computational experience is reported for real life problems.

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Examinando Artículos de Revista por Materia "1207 Investigación Operativa"