By Peter Keenan, associate professor, Centre for Business Analytics, University College Dublin.
Modelling has always taken advantage of the power of computing, and the enormous increase in computing power has allowed the use of ever more sophisticated modelling techniques. However, despite this growing computer power, modelling approaches have often only been capable of solving simplified versions of problems. While this simplification makes the problems computationally tractable, these simplifications often make theoretically efficient solutions of little value in the real world. To provide effective solutions for Business Analytics, we are interested not only in the theoretical power of the solution technique, but also in its actual fit with the real business problem. Faster computers will simply lead to an inappropriate answer in less time, if the problem modelled is not a useful representation of the one we actually want to solve.
By Pau Fonseca i Casas, professor, Technical University of Catalonia.
Environmental simulation models are difficult to handle due to the inherent complexity of the elements involved on the analyzed systems. How we can deal with the complexity of those systems? How can we work with the diversity of the languages and terminologies used by different experts? How can we allow an extensive Validation and Verification of such models? The use of formal languages and co-simulation techniques allow the combination of several simulation and optimization techniques in a single simulation engine, helping to improve system design concerning environmental issues. New methodologies are emerging, allowing to obtain optimal or sub-optimal solutions for these kind of systems without concessions on the necessary Validation and Verification processes. On the specific area of Smart Cities and Building energy management, different frameworks (e.g. NECADA) use this methodology to improve the sustainability in urban areas or buildings. This allows to combine IoT, Data Mining, Optimization, Simulation and other techniques through the formalized model.
By Belén Melián-Batista and J. Marcos Moreno-Vega, associate professors, University of La Laguna.
International freight plays an important role in the development and consolidation of important economic sectors such as trade, industry and tourism. The ports are critical infrastructures within multimodal transport networks that integrate maritime and terrestrial environments. They are also vulnerable to unforeseen events caused by nature or by deliberate or accidental human actions. The consequences range from the reduction of the productivity up to the temporary closure of the port.
In order to manage the risks and improve the robustness of the system, mechanisms that increase the resilience of these infrastructures are important. Resilience is the ability to withstand and recover intelligently from eventualities, facilitating the development of activities in the shortest possible time.
Tagged with: accidents
, natural disasters
By Rubén Ruiz, professor, Department of Applied Statistics, Operational Research and Quality, UPV; & Ángel A. Juan, associate professor, Computer Science Department, IN3 – UOC.
Data is everywhere. In the age of the internet we use data, computers, and statistics to analyze, measure, and compare everything: different strategies, policies, systems, processes, and even people. This allows us to be more informed and as a consequence, make better decisions. In a word, it makes us wiser than ever.
However, the ease of access to data and computers can also have some drawbacks if we are not cautious. Sometimes it is too easy to succumb to the temptation to compare apples with oranges, and consider the results of these comparisons as valid just because we are using some fancy math formulas, lots of Internet-based data sources, or powerful computers. Of course, extracting conclusions after comparing apples with oranges is a practice we should try to avoid.
Tagged with: citation
, impact factor
By Álvaro García Sánchez, professor, Technical School of Industrial Engineering, Technical University of Madrid.
Optimization problems in real world systems are a huge challenge and are a source of enjoyment and effort for Operation Research/Analytics (OR/A) modelers as well of satisfaction when delivering good quality solutions. Nevertheless, other compelling challenges go along with devising a good solving strategy itself during a project where there is a customer.
A first challenge is to gain the credibility from the manager who is running a system that may me improved thought OR/A models. When there is a chance for modeling a problem and gaining effectiveness and efficiency in some way, prior to modeling itself, first we need to prove or inspire trust in the incumbent manager. Past failures, the gap between the practitioners and the academic worlds and so many other reasons may be stoppers.
By Jesús E. Gabaldón, analytics manager, Accenture Centre of Excellence.
In recent years, analytic databases have become crucial in many areas since they allow to provide the necessary workforce in sectors like social media, marketing, Internet of Things, among many others. For instance, everyday situations like sharing information in Twitter or Facebook would not be possible without this technology.
In this area, Massively Parallel Processing (MPP) as well as HDFS and MapReduce architectures have evolved separately most of the time, and both of them are still running on different tracks. However, each one is serving different purposes. Hadoop has a long record in high performance computing but it easily becomes an inaccurate and slow tool for certain tasks. There are some SQL-on-Hadoop databases but they are still immature and quite SQL unfriendly.
Tagged with: analytics
, Massively Parallel Processing (MPP)
, private sector
, sharing information