Conferencias 2015 - Universidad Pública de Navarra

CONFERENCIAS PREVISTAS EN EL
AÑO 2016
DPTO DE ESTADÍSTICA E INVESTIGACIÓN OPERATIVA, UPNA
1. Ponente: Elias T. Krainski (Norwegian University Science & Technology)
y Haakon C. Bakka (Norwegian University of Science & Technology)
Fecha: Lunes-Miércoles del 22-24 de febrero
Tı́tulo: Curso derivadas parciales estocásticas
Resumen:
2. Ponente: Thomas Nowak (University of Graz, Austria)
Fecha: Miércoles 25 de mayo a las 12:30.
Tı́tulo: Life-Cycle Planning in Closed-Loop Supply Chains: A Study of
Refurbished Laptops
Resumen: Waste electrical and electronic equipment (WEEE) is one of
the fastest growing waste streams. Therefore, the reduction of discarded
electronic equipment is of immense importance in order to reduce virgin material consumption and hence the environmental impact associated
with the production and consumption of consumer electronics. Using the
market for new and refurbished laptops as a reference industry, a typical
life-cycle of a laptop including refurbishment and resale of the returned
product is modeled and analyzed in order to explore the related profitability. Therefore, we first investigate actual market prices of new and
refurbished laptops using data gathered from bestbuy.com. Subsequently,
we introduce a newsvendor model where we use the insights into pricing of
these products obtained from the empirical study. The model integrates
different reverse channels like recycling or disposal which have a crucial
impact on the original equipment manufacturer’s optimal decision making.
Our studies highlight how the return rate and fractions of returned cores
that are refurbished by the OEM as well as new and refurbished product prices are interrelated and influence the OEMs production decision
problem.
K eywords:Closed-Loop Supply Chains; Newsvendor Models; Refurbishing; Waste Electrical and Electronic Equipment
3. Ponente: Carlos Méndez (Universidad Litoral - CONICET, Argentina)
Fecha: Jueves 9 de junio a las 12:30h
Tı́tulo: Maritime logistics and transportation of multi-parcel chemical
tankers
Resumen: The cost-effective routing and scheduling of a fleet of multiparcel chemical tankers represents a central decision making process in
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both chemical and shipping industries. Ships designed for the transport
of liquid or gas in bulk are called tankers. Shippers seek to choose the
cargos to transport and determine the optimal route that the ship should
follow to maximize its profit. Due to determining the optimal assignment
and routing decisions of a large set of cargos transported by a ship fleet
is inherently NP-hard, real-world problems are either intractable or result in poor solutions when solving by pure optimization approaches. To
overcome this limitation, a new continuous time precedence-based MILP
mathematical formulation using heuristic-based algorithms and a column
generation technique is proposed. The applicability and efficiency of the
approaches are illustrated by solving a real case of study corresponding
to a sea-cargo shipping company operating in South-East Asia. Computational results show notable improvements and better performance when
compared to other alternative reported solution techniques.
K eywords: Ship routing and scheduling, MILP-based approach, Heuristic
techniques, Maritime transportation, Logistics
4. Ponente: Carlos Quintero Araujo (Universitat Oberta Catalunya, Barcelona)
Fecha: Miércoles 22 de junio a las 12:30h
Tı́tulo: Horizontal Cooperation in Logistics Network Design: Assessing
Cost Reduction and Environmental Impact
Resumen: This paper analyzes how different levels of horizontal cooperation (HC) practices can be employed in logistics network design
(LND). We study the impact of non-cooperative, semi-cooperative, and
full-cooperative scenarios on strategic and operational decisions such as:
the number of facilities to be opened, the assignment of customers to facilities, and the corresponding vehicle routing plans. For each scenario, a
different optimization problem arises and, therefore, solutions of different
quality can be obtained. We also propose a biased-randomized metaheuristic to solve the location routing problem. An extensive set of numerical
experiments illustrates the impact of HC practices on installation, delivery
and environmental costs.
K eywords: Biased randomization, integrated location routing problem,
iterated local search
5. Ponente: Celia Carrasco Gil, Lilian Benitez Ruiz y Ana Ruis Apastegui
(IES Benjamin de Tudela)
Fecha: Domingo 15 de mayo. Entrega de premios fase autonomica
Miércoles-Viernes del 29-1 julio. Fase nacional de Incubadora de Sondeos.
Tı́tulo: El último invierno: raro pero no muy caluroso.
Resumen: De manera reiterada estamos oyendo que este invierno habı́a
sido muy caluroso. Y, aunque de forma intuitiva nos parezca que es ası́, la
mejor forma de afirmarlo es disponer de datos y ver si es cierto o no. Los
datos históricos de climatologı́a han sido proporcionados por el Gobierno
de Navarra en su Web y por la Web de meteorologı́a. Se aplica la técnica
del contraste de hipótesis y se estudian los parámetros de interés, con los
que poder confrontar los datos históricos meteorológicos con los de este
invierno.
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6. Ponente: Eva K. Lee
Fecha: Lunes 25 de julio a las 10:00h
Tı́tulo: Computational Medicine and Big Data Analytic
Resumen: Mathematical modeling and computational methods have
long been cornerstones for advancement of business analytics in industrial, government, and military applications. They are playing key roles
in advancing and transforming medicine and healthcare delivery. In particular, multi-source data system modeling and computational big data
analytics and technologies play an increasingly important role in modern
healthcare enterprise. Many problems can be formulated into mathematical models and can be analyzed using sophisticated optimization, decision
analysis, and computational techniques. In this talk, we will share some of
our successes in early disease diagnosis, precision medicine optimal treatment planning design, and healthcare operations through innovation in
mathematical modeling and predictive big data analytics.
7. Ponente: Sally Brailsford
Fecha: Lunes 25 de julio a las 15:00h
Tı́tulo: Predicting patient flow in a pediatric intensive care unit
Resumen: The US healthcare industry has been facing rising costs for
many years. The Children’s Hospital of Wisconsin (CHW) in Milwaukee
wished to know whether savings could be made if an observation unit were
set up as an intermediate unit between the Paediatric Intensive Care Unit
(PICU) and the Acute Care Unit. This arose from a concern that in future, insurance companies might refuse to pay for PICU level of care if the
patient could have been safely treated elsewhere. This paper describes an
Excel-based analytic tool which enables clinicians to identify patients who
might be eligible for treatment outside the PICU, and then estimate the
financial impact of relocating them. Data mining techniques were used
to identify and group the patients/disease types selected for placement
outside of the PICU, as well as key resources and tasks involved in patient care and outcomes. The study focused on one specific reason for
admission, ingestion (accidental or deliberate) of toxic substances. A list
of procedures requiring PICU level of care was established through discussion with the PICU physicians, and these were used to classify patients
into two groups, those who should stay in the PICU and those who could
be safely treated in the observation unit. The cost analysis showed that a
predicted 87% savings could be made between the current situation and
the best scenario, i.e. if CHW were able to identify and relocate all eligible patients. A subsequent MSc project has extended this work by using
data available on admission to predict length of stay. This project also
resulted in a user-friendly Excel-based tool that uses routine data from
CHW information systems.
8. Ponente: Ying C MacNab
Fecha: Jueves 1 de septiembre a las 12:00h
Tı́tulo: On multidimensional Gaussian Markov Random fields and Bayesian
computation
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Resumen: Proposals of multivariate Gaussian Markov random field (MGMRF)
models have been advanced in tandem with developments of relevant computational solutions and strategies. The symmetric and positivity conditions for a MGMRF, or a class of MGMRFs that are typically defined by
full conditionals or as linear models of coregionalization, demand carefully
considered parameterization for identification and related computational
strategies. In this paper, some recent works on MGMRFs are reviewed,
with in-depth discussions on strategies for, and challenges in, Bayesian
computation. Within the context of analysis of multivariate spatial data
on finite lattice in general, and in the context of Bayesian disease mapping and small area estimation in particular, we discuss MGMRFs as prior
models or as data models within Bayesian hierarchical model framework.
Several examples are presented to illustrate recently proposed computational solutions and unresolved challenges.
9. Ponente: Eva Vallada (Universidad Politécnica de Valencia)
Fecha: Viernes 14 de octubre a las 12:30h
Tı́tulo: Heurı́sticas para el problema de secuenciación en máquinas paralelas con un recurso adicional
Resumen: El problema abordado consiste en secuenciar un conjunto de
n trabajos que han de ser procesados en una máquina de un conjunto formado por m máquinas. Cada trabajo consiste en una única tarea que ha
de realizarse en una de las máquinas. Las máquinas son no relacionadas, es
decir, el tiempo de proceso de los trabajos en las máquinas es diferente en
función de la máquina a la que se asigne. Además, se considera un recurso
adicional (recursos humanos, moldes, herramientas), que es limitado. En
este trabajo se proponen cinco heurı́sticas multi pasada para el problema
de secuenciación en máquinas paralelas no relacionadas con un recurso
adicional y el objetivo de minimizar el tiempo máximo de finalización o
makespan. Los métodos propuestos tienen una parte constructiva común,
basada en ocho reglas de asignación sin considerar la restricción del recurso adicional, por lo que la asignación obtenida es muy probable que
no sea factible desde el punto de vista del recurso adicional. Se aplica
un procedimiento de reparación con el objetivo de convertir en factible
la asignación y se proponen diferentes búsquedas locales para mejorar la
solución. Se realiza un extenso estudio computacional utilizando instancias pequeñas, medianas y grandes, obteniendo buenos resultados tanto
desde el punto de vista de la eficacia como de la eficiencia.
10. Ponente: Virgilio Gomez-Rubio (Universidad de Castilla-La Mancha)
Fecha: Lunes 17 de octubre a las 10:30h
Tı́tulo: Extending the Integrated Laplace Approximation
Resumen: The Integrated Nested Laplace Approximation and its associate R-INLA package provide a suitable framework for approximate
Bayesian inference. In particular, R-INLA will fit complex Bayesian hierarchical models in a fraction of the time required by other computational
intensive methods such as Markov Chain Monte Carlo. However, a limitation of INLA is that in order to fit a model it needs to be implemented
within R-INLA. Also, INLA only provides marginal inference of the model
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parameters and other related quantities. In this talk we will show how to
extend INLA (and R-INLA) by combining it with MCMC. We will provide an easy way to extend the number of models that R-INLA can fit,
as well as other other important topics such as (low dimension) multivariate inference and handling missing values in the covariates of regression
models.
11. Ponente: Kris Braekers (Hasselt University, Belgium)
Fecha: Miércoles 26 octubre a las 12:00h
Tı́tulo: Meta-heuristic approaches for Dial-A-Ride Problems
Resumen:Dial-A-Ride Problems (DARPs) arise in the context of demand
responsive transportation. They are concerned with the design of efficient
vehicle routes for transporting individual persons from specific origin to
specific destination locations. Service providers should find a balance between economic objectives (minimizing costs) and the human perspective
(offering high quality of service by adhering to strict time windows and
maximum ride times). Although dial-a-ride services are currently provided in many large cities, these services are expected to become even
more widely spread in the future due to the aging population and the
trend towards the development of ambulatory health care services. This
talk will highlight several meta-heuristic approaches that have been developed at Hasselt University to solve DARP variants. Considered extensions
to the classical DARP include multiple depots, heterogeneous (and configurable) vehicles, multiple user types and driver consistency. Applied solution frameworks include local search based methods (threshold accepting,
variable neighborhood descent) and large neighborhood search. The main
scientific results from a computational point of view as well as lessons
learned from a methodological point of view are presented. K eywords:
Vehicle Routing; Dial-A-Ride Problem; Meta-heuristic; Threshold Accepting; Large Neighborhood Search
12. Ponente:Aljoscha Gruler (Open University of Catalonia, Spain)
Fecha: Viernes 21 octubre a las 12:30h
Tı́tulo: A simheuristic based on Variable Neighborhood Search for Waste
Collection Problem under uncertainty
Resumen: Ongoing population growth in cities and increasing garage
production has made the optimization of waste collection a critical task
for local government. Route planning for waste collection can be formulated as extension of the well-known Vehicle Routing Problem (VRP), for
which a wide range of solution methodologies already exist in the literature. However, despite the fact that real-life applications are characterized by high levels of uncertainty, most works on waste collection focus on
simplified, deterministic versions of the problem. This talk presents a hybrid simheuristic algorithm to solve the waste collection problem (WCP)
with stochastic demands. First, an efficient Variable Neighborhood Search
metaheuristic for the deterministic version of the problem is presented.
Then, it is outlined how the combination of this algorithm with simulation constitutes an easy-to-implement approach to consider the WCP
under input uncertainty. Finally, it will be shown how the application
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of horizontal cooperation techniques between different waste management
service providers can be a further advance to reduce the negative impacts
of urban waste collection.
K eywords: Waste Collection; Smart Cities; Metaheuristics; Simulation;
Simheuristics
13. Ponente: Natalia Basan (Universidad Nacional del Litoral, Argentina)
Fecha: Jueves 3 noviembre a las 12:30h
Tı́tulo: Production scheduling optimization for power-intensive processes
with time-sensitive electricity prices
Resumen:Continuous power-intensive processes in air separation plant
can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed
based on a discrete-time scheduling formulation that allows modeling and
optimizing operating decisions either in a fixed or a rolling horizon scheme.
The main goal of this contribution is to find an optimal hourly schedule
for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world
electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort
considering a one-hour time grid and one-week time horizon.
K eywords: continuous power-intensive processes, air separation plant,
scheduling, MILP model, energy consumption cost
14. Ponente:
Fecha:
Tı́tulo:
Resumen:
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