Browsing by Autor "Edwin Montoya"

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Autonomous cycles of data analysis tasks for innovation processes in MSMEs
(Elsevier BV, 2022) Ana Gutiérrez; José Aguilar; Ana María Ortega; Edwin Montoya
Purpose The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs). Design/methodology/approach The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process. Findings In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry. Research limitations/implications It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks. Practical implications ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement. Originality/value The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.
Many-Objective Optimization Approach using Surrogate Models in Rotational Cattle Grazing
(2025) Marvin Jiménez Narváez; Jose Aguilar; Juan Manuel Montoya; Edwin Montoya
In the context of many-objective problems, one of the most important problems is to be able to efficiently model and evaluate the different objectives of the problem. A strategy to speed up the computation, as well as to manage the uncertainties due to partial knowledge of the context, is to use surrogate models. The objective of this paper is to evaluate the hybrid use of surrogate models in the context of a many-objective optimization problem for livestock management. In particular, we propose to use hybrid objective functions, in which parts of the objective function originally constructed analytically are replaced by data-driven surrogate models. Specifically, we explore several hybrid schemes, where in each we combine different parts of the analytical objective function with other data-driven parts. Preliminary results show that the hybrid optimization models studied possess a competitive performance quality against the original purely analytical model, becoming an interesting proposal to manage the computational times and uncertainty of environments such as livestock farming. These results show the great potential of using models built with machine learning techniques to replace analytically constructed objective functions that are not always able to absorb the non-deterministic nature of livestock grazing, and represent an opportunity to further explore their usefulness in this context.