The research team is located in the Faculty of Sciences of the University of Cadiz, at the Campus of Puerto Real, and integrated within the University Institute of Research for Sustainable Social Development-INDESS. Since its creation in 2006, it has grown to currently have 10 members, of which 8 are doctors, 6 of them women.
One of the lines of research on which most work is being done in recent years is related to the planning of logistics systems. We have been making applications of our results to problems arising from real situations in the industry. Using Operational Research techniques, we analyse any problem that integrates one or more of the relevant elements in the planning. The objective is to create realistic mathematical models, which effectively help decision-making and system monitoring. The fundamental tools at our disposal are mathematical programming and simulation.
In order to achieve a better management of resources, it is necessary to analyse a large amount of data of very different types. To obtain effective solutions it is necessary to apply Big Data techniques. Our group works by providing models, tools and procedures to solve optimization problems associated with intensive data classification, paying special attention to the development of flexible models and the selection of features in supporting vector machines.
Another of the basic lines that are studied in the group framed within the Statistics is that of the statistical analysis of data, exploratory analysis techniques are proposed with the aim of describing starting states in different environments, very useful in the business field for the detection of problems. As well as prediction studies, focusing on the essential factors of the study in order to improve decision-making in the business environment. All the members of the group are trained in this type of techniques. In the actuarial field, a line of research is currently being developed with some members in which various premium principles are proposed that incorporate the insurer's risk aversion.
Our group works by providing models, tools and procedures to solve optimization problems associated with intensive data classification, paying special attention to the development of flexible models and feature selection on supporting vector machines. In order to do that, we use techniques of Linear and Nonlinear Integer Mathematical Programming.
The experience of its members in algorithmic aspects of optimization problems is outstanding, both from the point of view of the development of resolution procedures (exact and heuristic), and in their corresponding implementation and subsequent computational analysis. In this group, the experience in the study of probability distributions, fundamental to approach the simulation tasks, also stands out.
Another of the basic lines that are studied in the group framed within the Statistics is that of the statistical analysis of data, exploratory analysis techniques are proposed with the aim of describing starting states in different environments, very useful in the business field for the detection of problems. As well as prediction studies, focusing on the essential factors of the study in order to improve decision-making in the business environment. All the members of the group are trained in this type of techniques. In the actuarial field, a line of research is currently being developed with some members in which various premium principles are proposed that incorporate the insurer's risk aversion.
- Study of cost optimization in the production chain of the company “ECOLÓGICOS Y IV GAMA" (OT2008/125). C: A. Castaño.
- Study and search of optimal locations for the location of a new point of sale of a chain of restaurants. (OT2008/126). C: A.M. Rodríguez-Chía