Abstract
The group of regions with common similarities allow the improvement of its competences management, support its integration processes, as well as strengthen the social and economic development of the regions that form a group. The analysis of regions with multidimensional characteristics, make necessary the application of concepts, models and algorithms that allow the analysis of ambiguous variables. The presented model seeks to contribute to an informed decision making, closer to reality while identifying those regions that because of its characteristics, share common features to relatively higher levels. The goal of this work is to design a process of grouping regions from the analysis of sustainable indicators, this will allow us maximize the resources in amplitude and quantity with the purpose to generate synergies in order to take the maximum advantage of the capacities of development and well-being. To reach such a goal, a methodological approximation based on Pichat’s algorithm is done using sustainable development indicators of each region as a reference and suggesting the degree of similarity among the regions so the determination of similar groups is possible.
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Pinto López, I.N., Gil Lafuente, A.M., Sánchez Flores, G. (2018). Pichat’s Algorithm for the Sustainable Regional Analysis Management: Case Study of Mexico. In: Berger-Vachon, C., Gil Lafuente, A., Kacprzyk, J., Kondratenko, Y., Merigó, J., Morabito, C. (eds) Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Studies in Systems, Decision and Control, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-319-69989-9_20
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