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Dive into the research topics where Adrián M. Aguirre is active.

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Featured researches published by Adrián M. Aguirre.


Computers & Chemical Engineering | 2012

Improving supply chain planning in a competitive environment

Miguel Zamarripa; Adrián M. Aguirre; Carlos A. Méndez; Antonio Espuña

Abstract This work extends the use of a Mixed Integer Linear Programming (MILP) model, devised to optimize the Supply Chain planning problem, for decision making in cooperative and/or competitive scenarios, by integrating these models with the use of the Game Theory. The system developed is tested in a case study based in previously proposed Supply Chain, adapted to consider the operation of two different Supply Chains (multi-product production plants, storage centers, and distribution to the final consumers); two different optimization criteria are used to model both the Supply Chains benefits and the customer preferences, so both cooperative and non-cooperative way of working between both Supply Chains can be considered.


Computer-aided chemical engineering | 2010

A Novel Optimization Method to Automated Wet-Etch Station Scheduling in Semiconductor Manufacturing Systems

Adrián M. Aguirre; Carlos A. Méndez

Abstract This work addresses the short-term scheduling of one of the most critical stages in the semiconductor industry, the automated wet-etch station (AWS). An efficient MILP-based computer-aided tool is developed in order to achieve a proper synchronization between the activities of sequential chemical and water baths and limited automated wafers lot transfer devices. The major goal is to find the optimal integrated schedule that maximizes the whole process productivity without generating wafer contamination.


Computers & Chemical Engineering | 2011

A novel optimization method to automated wet-etch station scheduling in semiconductor manufacturing systems

Adrián M. Aguirre; Carlos A. Méndez; Pedro M. Castro

Abstract This work addresses the short-term scheduling of one of the most critical stages in the semiconductor industry, the automated wet-etch station (AWS). An efficient MILP-based computer-aided tool is developed in order to achieve a proper synchronization between the activities of sequential chemical and water baths and limited automated wafers lot transfer devices. The major goal is to find the optimal integrated schedule that maximizes the whole process productivity without generating wafer contamination. Several examples are successfully solved to illustrate the capabilities of the proposed method.


BMC Health Services Research | 2014

Managing daily surgery schedules in a teaching hospital: a mixed-integer optimization approach

Raul Pulido; Adrián M. Aguirre; Álvaro García-Sánchez; Carlos A. Méndez

BackgroundThis study examined the daily surgical scheduling problem in a teaching hospital. This problem relates to the use of multiple operating rooms and different types of surgeons in a typical surgical day with deterministic operation durations (preincision, incision, and postincision times). Teaching hospitals play a key role in the health-care system; however, existing models assume that the duration of surgery is independent of the surgeon’s skills. This problem has not been properly addressed in other studies. We analyze the case of a Spanish public hospital, in which continuous pressures and budgeting reductions entail the more efficient use of resources.MethodsTo obtain an optimal solution for this problem, we developed a mixed-integer programming model and user-friendly interface that facilitate the scheduling of planned operations for the following surgical day. We also implemented a simulation model to assist the evaluation of different dispatching policies for surgeries and surgeons. The typical aspects we took into account were the type of surgeon, potential overtime, idling time of surgeons, and the use of operating rooms.ResultsIt is necessary to consider the expertise of a given surgeon when formulating a schedule: such skill can decrease the probability of delays that could affect subsequent surgeries or cause cancellation of the final surgery. We obtained optimal solutions for a set of given instances, which we obtained through surgical information related to acceptable times collected from a Spanish public hospital.ConclusionsWe developed a computer-aided framework with a user-friendly interface for use by a surgical manager that presents a 3-D simulation of the problem. Additionally, we obtained an efficient formulation for this complex problem. However, the spread of this kind of operation research in Spanish public health hospitals will take a long time since there is a lack of knowledge of the beneficial techniques and possibilities that operational research can offer for the health-care system.


Computer-aided chemical engineering | 2013

Hybrid time representation for the scheduling of energy supply and demand in smart grids

Javier Silvente; Adrián M. Aguirre; Guillem Crexells; Miguel Zamarripa; Carlos A. Méndez; Moisès Graells; Antonio Espuña

Abstract A new optimization model is presented for the short-term management of the energy supply and demand in smart grids. The detailed model includes a flexible demand profile in order to manage the energy requirements by incorporating penalizations in the economic objective function for delays in satisfying energy demand. The MILP model for the optimization of deterministic scenarios is reformulated in order to incorporate discrete and hybrid time representations. This approach allows considering a different granularity of the problem. Finally, the improved performance of the hybrid approach introduced is shown by comparing the performance of these two time representations.


Computers & Chemical Engineering | 2012

An improvement-based MILP optimization approach to complex AWS scheduling

Adrián M. Aguirre; Carlos A. Méndez; G. Gutierrez; César de Prada

Abstract The automated wet-etch station (AWS) is one of the most critical stages of a modern semiconductor manufacturing system (SMS), which has to simultaneously deal with many complex constraints and limited resources. Due to its inherent complexity, industrial-sized automated wet-etch station scheduling problems are rarely solved through full rigorous mathematical formulations. Decomposition techniques based on heuristic, meta-heuristics and simulation-based methods have been traditionally reported in literature to provide feasible solutions with reasonable CPU times. This work introduces an improvement MILP-based decomposition strategy that combines the benefits of a rigorous continuous-time MILP (mixed integer linear programming) formulation with the flexibility of heuristic procedures. The schedule generated provides enhanced solutions over time to challenging real-world automated wet etch station scheduling problems with moderate computational cost. This methodology was able to provide more than a 7% of improvement in comparison with the best results reported in literature for the most complex problem instances analyzed.


Computer-aided chemical engineering | 2012

Integration of Mathematical Programming and Game Theory for Supply Chain Planning Optimization in Multi-objective competitive scenarios

Miguel Zamarripa; Adrián M. Aguirre; Carlos A. Méndez; A. Espuña

Abstract This work develops a multi-objective MILP (Mixed Integer Linear Programming) model, devised to optimize the planning of supply chains using Game Theory optimization for decision making in cooperative and/or competitive scenarios. Three different optimization criteria are considered (total cost, tardiness and expenses of the buyers for the competitive problem). The multi objective problem has been solved using the Pareto frontier solutions, and both cooperative and non cooperative scenarios between supply chains are considered, so multiple optimization tools/techniques have been combined to analyze the different trade-offs associated to the resulting decision making: Game Theory, MILP based approach and Pareto frontiers. The resulting model is tested in a case study, based on the operation of two different supply chains in both competitive and cooperative situations.


Computer-aided chemical engineering | 2012

MILP-based Approach for the Scheduling of Automated Manufacturing System with Sequence-Dependent transferring times

Adrián M. Aguirre; Carlos A. Méndez; Pedro M. Castro; César de Prada

Abstract A general MILP-based model is presented for the scheduling of multiple products in Automated Manufacturing Systems. The proposed model addresses the scheduling of multiple processing operations in several stages considering recycle flows and sequence-dependent transfer times in a single automated-material handling robot. A real-world industrial application problem is solved to demonstrate the effectiveness of the proposed approach.


Computer-aided chemical engineering | 2011

A robust MILP-based approach to vehicle routing problems with uncertain demands

Adrián M. Aguirre; Mariana Evangelina Coccola; Miguel Zamarripa; Carlos A. Méndez; A. Espuña

Abstract The Vehicle Routing Problem with Stochastic Demands (VRPSD) has attracted the attention of the research community over the last decades by introducing the random behavior of the demand into the traditional routing problem. Many related works were focusing on providing suitable approaches of this large combinatorial problem for many different cases of uncertainly demand. Moreover, exact approaches that were developed up to now provide reliable results for specific demand values, e.g. using the highest demand value or the most expected value, but these solutions do not consider the concurrent effect of many possible scenarios into the objective function. So, the real necessity of more efficient and reliable approaches for this problem that provides optimal solutions for small and medium size cases in a reasonable time and also that response consistently to the random behavior of the demand has been clearly appeared in the last years ( Novoa and Storer, 2009 ). In this work a robust MILP-based formulation for the VRPSD problem is developed. The main goal of this method is to find a reliable solution that provides an optimal result considering the occurrence of many possible scenarios in simultaneous.


International Journal of Production Research | 2014

A hybrid scheduling approach for automated flowshops with material handling and time constraints

Adrián M. Aguirre; Carlos A. Méndez; Pedro M. Castro

Flowshop scheduling problems have been extensively studied by several authors using different approaches. A typical flowshop process consists of successive manufacturing stages arranged in a single production line where different jobs have to be processed following a predefined production recipe. In this work, the scheduling of a complex flowshop process involving automated wet-etch station from semiconductor manufacturing systems requires a proper synchronisation of processing and transport operations, due to stringent storage policies and fixed transfer times between stages. Robust hybrid solution strategies based on mixed integer linear programming formulations and heuristic-based approaches, such as aggregation and decomposition methods, are proposed and illustrated on industrial-scale problems. The results show significant improvements in solution quality coupled with a reduced computational effort compared to other existing methodologies.

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Dive into the Adrián M. Aguirre's collaboration.

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Carlos A. Méndez

National Scientific and Technical Research Council

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Miguel Zamarripa

Polytechnic University of Catalonia

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Antonio Espuña

Polytechnic University of Catalonia

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A. Espuña

Polytechnic University of Catalonia

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Songsong Liu

University College London

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Javier Silvente

Polytechnic University of Catalonia

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