Redes Celulares 5G
26 marzo, 2019
Advanced Methods in Operations Research for Logistics and Transportation
5 noviembre, 2019

Avdanced Methods in Operations Research for Logistics and Transportation

In the context of decision-making processes, we use Operations Research methods to understand, predict and optimize the behavior of real-life systems through mathematical models. Operations Research techniques are designed to tackle problems with practical meaning, which are typically very complex. These models and methods have been applied in numerous contexts such as defining public and private policies, and planning processes for government and industry with an exceptionally broad spectrum.

Nowadays, in the era of information and data, the development of technological tools that support the decision-making process gains vital importance, which in turn, reaffirms the value of studying Operations Research methods. The area of Logistics and Transportation systems is a special case where the technological growth is evident in the last two decades. There, predicting patterns and optimizing decisions plays a major role in the overall operations. Moreover, this area has been a particular source of study for researchers and practitioners in Operations Research. The problems encountered usually represent a high-value decision but also, they possess an intrinsic mathematical structure that provoke a detailed scientific study.

Having in mind today’s global requirements in the development of algorithms and efficient solution methods to problems that appear in the contexts of Logistics and Transportation we have elaborated an initiative to promote the better understanding of cutting-edge technology and the scientific collaboration for the design and creation of new models and methods in Operations Research.

General Objectives
  • To promote scientific collaboration in research lines that focus on advanced methods in Operations Research
  • To present state-of-the-art methodologies and problems within the context of Logistics and Transportation.
Specifics Objectives
  • To present concrete applications in Logistics and Transportation where advanced optimization and machine learning techniques are applied.
  • To stablish potential future lines of research.
  • To communicate recent research projects of the participants and the invited speakers.
  • To introduce state-of-the-art solution methods for various optimization and prediction problems in Logistics and Transportation.
Value proposal

In the context of decision-making processes, we use Operations Research methods to understand, predict and optimize the behavior of real-life systems through mathematical models. Operations Research techniques are designed to tackle problems with practical meaning, which are typically very complex. These models and methods have been applied in numerous contexts such as defining public and private policies, and planning processes for government and industry with an exceptionally broad spectrum.

Nowadays, in the era of information and data, the development of technological tools that support the decision-making process gains vital importance, which in turn, reaffirms the value of studying Operations Research methods. The area of Logistics and Transportation systems is a special case where the technological growth is evident in the last two decades. There, predicting patterns and optimizing decisions plays a major role in the overall operations. Moreover, this area has been a particular source of study for researchers and practitioners in Operations Research. The problems encountered usually represent a high-value decision but also, they possess an intrinsic mathematical structure that provoke a detailed scientific study.

Having in mind today’s global requirements in the development of algorithms and efficient solution methods to problems that appear in the contexts of Logistics and Transportation we have elaborated an initiative to promote the better understanding of cutting-edge technology and the scientific collaboration for the design and creation of new models and methods in Operations Research.

Method

There will be four short courses or modules in recent topics of Operations Research. Each module consists of 6 hours of lecture and will be taught by a different expert. There will be time for questions and comments from the participants. We will also offer a 6 hours hands-on workshop on specialized optimization software.

There will be parallel sessions for short talks and poster presentations from the research projects of the participants.

All the modules and workshop will be in English. The presentations from the participants must be either in English or in Spanish with the slides in English.

Addressed to

The school is targeted to all the members of the academic community and practitioners who are interested in advanced topics in Operations Research. We expect the focus of participants to be graduate students from the areas of mathematics, industrial engineering and computer science. It is important the interested applicant has some knowledge of Operations Research methods.

Academic Content
Modules

Models and Decomposition Methods for Large-Scale Network Optimization (Prof. Ivan Contreras)

Abstract:
Network optimization problems lie at the hearth of network design planning in transportation and telecommunications systems. This series of talks focus on a challenging class of problems referred to as general network design, which offers a unified view of integrated facility location, and network design. Their main difficulty stems from the inherent interrelation between two levels of the decision process. The first level considers design decisions such as the selection of nodes to locate facilities and the activation of links to connect nodes. The second level considers tactical decisions such as the assignment of nodes to facilities and the routing of flows through the network. We present an overview of some of the most prominent mathematical programming formulations that have been used in combination with decomposition methods to develop state-of-the-art exact solution algorithms capable of solving large-scale instances of three important classes of problems involving both linear and nonlinear cost functions: hub network design, multi-level facility location, and multi-commodity network design. We highlight the connections between Lagrangean relaxation, Dantzig-Wolfe decomposition, Benders decomposition, and related primal relaxations in the context of such problems. We also point out to several algorithmic refinements that have been used to accelerate the convergence of such decomposition methods. Practical implementation guidelines to improve their overall performance are discussed.

Section B – Virtual Reality in Industrial Environment

In this section, we will explain the subject of virtual reality, and its importance in industrial environments with applications particularly in the energy sector. The VR is a computer-generated scenario that simulates a realistic experience through which one interacts with a seemingly real or physical way.

The Javeriana University have created the CAVE room "Cave Assisted Virtual Environment" for use in 3D and immersive engineering applications. The CAVE will work for job training aimed for workers, it offers the possibility to move safely around dangerous places and learn how to deal with emotions, while experimenting the best solutions while far away from the real dangers and the reduction of Musculoskeletal Disorders MSDs

Lecturer/Teacher: Mondragón, Iván. MSc, PhD

Section C – Digital Ergonomics. Applications in Industry

In this section of the course, the application of digital environments around ergonomics will be presented. For this, we will have the application of these concepts on the automotive industry showing the main strengths and challenges at the time of implementation

Lecturer/Teacher: Hensel-Unger, Ralph, Dr.-Ing.

Este temario puede tener variaciones, siendo una propuesta de capacitación flexible, que busque el máximo desempeño de los alumnos, de acuerdo con las necesidades específicas de los mismos.

Speakers
Dr.-Ing. Ralph Hensel-Unger (Germany)

Leader of the implementation of exoskeletons support strategy for VW-group and Audi, at the Industrial Engineering Methods Department.

Business Administration and Electrical Engineering at Chemnitz University of Technology. Doctoral degree in Engineering. Topic of doctoral thesis: “Organizational concept for the implementation of Industrial Engineering in different countries considering cultural differences”.

Saavedra-Robinson, Luis. IE, PhD:

Industrial Engineer from Pontificia Universidad Javeriana Bogotá. PhD in Ergonomics from the Polytechnic University of Catalonia, Barcelona, Spain. Consulting experience in hygiene industrial at oil & gas industry. As a researcher, he looking for the relationship between industrial process, methods and productivity with ergonomics conditions at the workplace, recollecting, analyzing and interpreting a Biomechanical, Anthropometrical and Physiological data for different projects on several sectors: Flowers, Automobile, Sugar Cane, Construction, Foods & Grocery, and Transport among others. As an Assistant Professor, he was the Industrial Engineering undergraduate degree director in Cali, Colombia, where, he leads the international accreditation ABET for the academic program, coordinated the redesign of the curriculum and participated in the national industrial engineering networks (ACOFI). His recent work aims to relate human factors to new trends in the industry (human modeling in industrial environments, industry 4.0, logistics and others).

Mondragón, Iván. MSc, PhD:

Electrical engineer from Universidad Nacional de Colombia, (October 2002). He joined the master program at Universidad de los Andes (Colombia) obtaining a M.Sc. in Electronics and Computers Engineering in May 2005. From 2005 to 2006 he worked as Power Transformers Test Field Engineer at Siemens Andina S.A. (Colombia). After it, he moved to Computer Vision Group at DISAM -ETSII- Universidad Politécnica de Madrid (Spain) obtaining a Ph.D degree in Automatic and Robotics in November 2011. While completing his Ph.D he gained extensive experience with Unmanned Aerial Vehicles and in particular in vision techniques for control and navigation of Autonomous Helicopter and Multirotor platforms. From August 2013 to February 2019, he collaborates as editor of Journal of Intelligent & Robotic Systems JINT. Since 2013, he is a full time professor and director of the Industrial Automation Technology Center (CTAI), Department of Industrial Engineering at Pontificia Universidad Javeriana. He is currently working on computer vision applied to Unmanned Aerial Vehicles as well as Flexible Manufacturing Systems FMS, Quality Inspection, virtual reality (CAVE system) and Industry 4.0.

Ficha Técnica

  • Fecha inicio:
    25 | 06 | 2019
  • Fecha fin:
    29 | 06 | 2019
  • Duración:
    40 horas
  • Horario:
    Martes a Sábado 8:00 am a 6:00 pm
  • Inversión:
    $1.295.000 COP/
    $ 432 USD
  • * El valor para estudiantes PUJ será el equivalente a dos créditos académicos.

Descuentos

4% por pronto pago en curso o diplomados, cancelando 30 días calendario previos a la fecha de inicio (acumulable con otros descuentos)

10% egresados, afiliados a Cafam y afiliados a IEEE

15% para grupos de 3 a 5 participantes en el mismo curso o diplomado

20% para grupos de 6 personas en adelante, y en el tercer curso o diplomado realizado consecutivamente

Forma de pago: Efectivo, cheque de gerencia, tarjeta de crédito (recibimos todas las tarjetas, cuenta de cobro).