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Agustín Martín, Alba

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Agustín Martín

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Alba

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Estadística e Investigación Operativa

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0000-0001-9173-1906

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810167

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2016 - 201932020 - 20231
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Now showing 1 - 4 of 4
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    PublicationOpen Access
    Using biased randomization for trajectory optimization in robotic manipulators
    (Springer, 2016) Agustín Martín, Alba; Olivares, Alberto; Staffetti, Ernesto; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
    We study the problem of optimization of trajectories for a robotic manipulator, with two degrees of freedom, which is constrained to pass through a set of waypoints in the workspace. The aim is to determine the optimal sequence of points and continuous optimal system trajectory. The actual formulation involves an optimal control problem of a dynamic system within integer variables that model the waypoints constrains. The nature of this problem, highly nonlinear and combinatorial, makes it particularly difficult to solve. The proposed method combines a meta-heuristic algorithm to determine the promising sequence of discrete points with a collocation technique to optimize the continuous path of the system. This method does not guarantee the global optimum, but can solve instances of dozens of points in reasonable computation time.
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    PublicationOpen Access
    An inventory-routing problem with stochastic demand and stock-out: a solution and risk analysis using simheuristics
    (IEEE, 2019) Onggo, Bhakti Stephan; Juan Pérez, Ángel Alejandro; Panadero, Javier; Corlu, Canan Gunes; Agustín Martín, Alba; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    Supply chain operations have become more complex. Hence, in order to optimise supply chain operations, we often need to simplify the optimisation problem in such a way that it can be solved efficiently using either exact methods or metaheuristics. One common simplification is to assume all model inputs are deterministic. However, for some management decisions, considering the uncertainty in model inputs (e.g., demands, travel times, processing times) is essential. Otherwise, the results may be misleading and might lead to an incorrect decision. This paper considers an example of a complex supply chain operation that can be viewed as an Inventory-Routing Problem with stochastic demands. We demonstrate how a simheuristic framework can be employed to solve the problem. Further, we illustrate the risks of not considering input uncertainty. The results show that simheuristics can produce a good result, and ignoring the uncertainty in the model input may lead to sub-optimal results.
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    PublicationOpen Access
    Optimizing airline crew scheduling using biased randomization: a case study
    (Springer, 2016) Agustín Martín, Alba; Gruler, Aljoscha; Armas, Jesica de; Juan, Ángel A.; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
    Various complex decision making problems are related to airline planning. In the competitive airline industry, ecient crew scheduling is hereby of major practical importance. This paper presents a metaheuristic approach based on biased randomization to tackle the challenging Crew Pairing Problem (CPP). The objective of the CPP is the establishment of ight pairings allowing for cost minimizing crew- ight assignments. Experiments are done using a real-life case with dierent constraints. The results show that our easy-to-use and fast algorithm reduces overall crew ying times and the necessary number of accompanying crews compared to the pairings currently applied by the company.
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    PublicationOpen Access
    Robots for elderly care: review, multi-criteria optimization model and qualitative case study
    (MDPI, 2023) Sawik, Bartosz; Tobis, Sławomir; Baum, Ewa; Suwalska, Aleksandra; Kropińska, Sylwia; Stachnik, Katarzyna; Pérez-Bernabeu, Elena; Cildoz Esquíroz, Marta; Agustín Martín, Alba; Wieczorowska-Tobis, Katarzyna.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
    This paper focuses on three areas: the first is a review of current knowledge about social and service robots for elderly care. The second is an optimization conceptual model aimed at maximizing the efficiency of assigning robots to serve the elderly. The proposed multi-criteria optimization model is the first one proposed in the area of optimization for robot assignment for the elderly with robot utilization level and caregiver stress level. The third is the findings of studies on the needs, requirements, and adoption of technology in elderly care. We consider the use of robots as a part of the ENRICHME project for long-term interaction and monitoring of older persons with mild cognitive impairment, to optimize their independence. Additionally, we performed focus group discussions (FGD) to collect opinions about robot-related requirements of the elderly and their caregivers. Four FDGs of six persons were organized: two comprising older adults, and two of the other formal and informal caregivers, based on a detailed script. The statements of older participants and their caregivers were consistent in several areas. The analysis revealed user characteristics, robot-related issues, functionality, and barriers to overcome before the deployment of the robot. An introduction of the robot must be thoroughly planned, include comprehensive pre-training, and take the ethical and practical issues into account. The involvement of future users in the customization of the robot is essential.