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Item type:Publication, A contribution of fuzzy logic to sustainable tourism through a case analysis in Brazil(IOS Press, 2020-09-08)Society is increasingly concerned about environmental, social and economic issues. According to the World Tourism Organization, over the past six decades, tourism has experienced a continuous expansion and diversification to become one of the fastest-growing economic sectors in the world. Furthermore, studies affirm the complexity of the tourism sector and the fact that sustainable development depends on various topics that are not correctly identified by managers and policymakers. For these reasons, this paper aims to reflect on the effects of tourism and to propose alternatives that can be sustainably managed. In terms of results, knowledge gaps have been identified and, through a case analysis in Brazil, the forgotten effects of tourism activity that can have an impact on sustainable development have been exposed. Also, an algorithm has been presented to manage uncertainty and facilitate decision-making. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Fuzzy Boundaries in Start-up Firms Industries. A Social Network Analysis(Alberto Hurtado University, 2020-12-01)This paper aims to explore and describe the way in which startup firms are grouped into industries. To this end, a quantitative research approach is presented, applying a social network analysis to a sample of Pacific Alliance startups, which were recorded in CrunchBase, considering their operational activities as linkage criteria. In this way, this document offers a new application to social network analysis to demonstrate the need for a different way of classifying startups that goes beyond the industry boundaries established by the traditional classification systems. It also shows that Pacific Alliance startup industries are structured according to a pattern of dominant activity, applied technology and specific use. In addition, there is a concentration on mature or declining startup industries, while growing industries are left in second order. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Sustainable management of the supply chain based on fuzzy logic(Bellwether Publishing, Ltd., 2021-01-01)Companies face a number of management challenges, and decision makers must adopt new approaches that consider sustainable development in their operations. In this context, the article aims to address sustainable supply chain management and propose solutions based on a fuzzy logic. Three distance measurement algorithms are applied to evaluate and classify suppliers in a consumer goods industry. The results demonstrate the usefulness of the algorithms in decision-making and bring a contribution to the sustainable development of companies. Furthermore, it supports future studies on sustainable management, the supply chain, and the application of algorithms to sustainability. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analytics under uncertainty: a novel method for solving linear programming problems with trapezoidal fuzzy variables(Springer Science+Business Media, 2021-11-23)Linear programming (LP) has long proved its merit as the most flexible and most widely used technique for resource allocation problems in various fields. To solve an LP problem, we have traditionally considered crisp values for the parameters, which are unrealistic in real-world decision-making under uncertainty. The fuzzy set theory has been used to model the imprecise parameter values in LP problems to overcome this shortcoming, resulting in a fuzzy LP (FLP) problem. This paper proposes a new method for solving fuzzy variable linear programming (FVLP) problems in which the decision variables and resource vectors are fuzzy numbers. We show how to use the standard simplex algorithm to solve this problem by converting the fuzzy problem into a crisp one once a linear ranking function is chosen. The novelty of the proposed model resides in that it requires less effort on fuzzy computations as opposed to the existing fuzzy methods. Furthermore, to solve the FVLP problem using the existing methods, fuzzy arithmetic operations and the solution to fuzzy systems of equations are required. By contrast, only arithmetic operations of real numbers and the solution to crisp systems of equations are required to solve the same problem with the method proposed in this study. Finally, a transportation case study in the coal industry is presented to demonstrate the applicability of the proposed algorithm. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A fuzzy project buffer management algorithm: A case study in the construction of a renewable project(Taylor & Francis, 2022-03-09)One of the major problems with projects is that they are not completed according to schedule. Uncertainty always exists at the heart of real-world project scheduling problems. This paper introduces a fuzzy project buffer management (FPBM) algorithm which is a combination of the adaptive procedure with resource tightness (APRT) and fuzzy failure mode and effects analysis (FFMEA) methods. This paper aims to present an efficient model for project buffer sizing by taking FFMEA into account to reach a more realistic schedule. In this research, for increasing the efficiency of the APRT method, the FFMEA technique is simultaneously applied with them. This research was carried out as a case study in a renewable energy (RE) project. The methodology of this research consists of two phases. The first phase is the implementation of the APRT buffer sizing method. In the second phase of the research methodology, the fuzzy FMEA method is implemented. To validate the proposed model, the results are compared to several buffer management models proposed recently. Also, the results were compared with the results of similar projects. The findings show that considering the fuzzy FMEA technique in the APRT method, a more realistic schedule was obtained in this project. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The strengthening of corporate governance based on applied fuzzy logic(John Wiley and Sons Ltd, 2022-09-01)Despite advances in research on corporate governance, there are still knowledge gaps. The article aims to broaden the debate on strengthening corporate governance and propose a tool to facilitate decision‐making. The research is novel because of the engagement of 117 master's students from a business school, contributing to competency‐based learning on Good Corporate Governance (GCG). This is applied research with the explanatory objective and quantitative approach through modeling and simulation. The OWA Operator assesses GCG principles' adequacy and reveals a ranking of 28 enterprises listed on the Lima Stock Exchange in corporate governance, increasing transparency and reducing risks. The results indicate that six enterprises would be solid in the GCG, and the corporate governance should consider strategic capability, fair dealing, transparency, and good social responsibility practices. The main contributions are reducing the identified knowledge gaps and proposing actions to strengthen governance. The authors suggest promising lines of research.3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Fuzzy data-driven scenario-based robust data envelopment analysis for prediction and optimisation of an electrical discharge machine's parameters(Elsevier Ltd, 2022-05-01)An electrical discharge machine (EDM) has a high impact on production management, with its process having many advantages over conventional machining processes, including the ability of the machine to create very high-quality material that is intricate to inner industrial sections. This study investigates the impact of EDM machining parameters on the volumetric flow rate, electrode corrosion percentage, and surface roughness. These machining parameters are increasingly important for the quality of the final product, leading to higher customer satisfaction and greater market share of the company. Due to dynamic changes in the machine's parameters and production environmental changes, using an uncertain model is inevitable. To investigate the machining data under uncertainty, a mathematical modelling approach based on the fuzzy possibility regression integrated (FPRI) model is developed. One advantage of the proposed model is that it is able to predict the surface roughness, volumetric flow rate, and corrosion percentage of the electrode. An adaptive-network-based fuzzy inference system (ANFIS) is applied to achieve the optimal levels of each output. Since the results and numbers obtained from the neural network are uncertain and their distribution is not clear, a robust data envelopment analysis approach (RDEA) is employed to select the best tuned-level of the parameters. The findings confirm the accuracy and reliability of the proposed method for prediction and optimisation of the EDM's parameters and encourage further tests for other production and supply chain applications. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bibliometric review of research on decision models in uncertainty, 1990-2020(John Wiley and Sons Ltd, 2022-10-01)Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision-making. The decision-maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Socio-economic and health management of pandemics based on forgotten effects theory(Taylor & Francis, 2022-04-04)Intense and frequent changes increase uncertainty and complexity in decision-making. The COVID-19 pandemic exacerbates this situation. Therefore, the decision-maker seeks to reduce risks and meet these challenges. The manuscript aims to identify cause-effect relationships between variables affecting countries and changes caused by the COVID-19 pandemic and propose an algorithm to facilitate decision-making by identifying forgotten effects. The authors use thematic analysis to synthesize the semi-systematic literature review findings. The applied research uses a quantitative approach through modeling and simulation. The results highlight that the pandemic effects are associated with causes such as health care, political and economic stability, social justice, and the level of corruption. Decision-makers must prioritize the management of these variables guided by science. The main contribution is to show an algorithm that identifies forgotten effects in pandemics' socio-economic and health management, preventing future crises. In addition, the study advances the frontier of knowledge by addressing identified gaps and contributes to academia and policy makers. The most critical limitation is the number of variables included in this research. Future investigations could include analyses on the impact of climate change and sustainable development of nations and country-specific studies on the forgotten effects of the COVID-19 pandemic. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An efficient intelligent intrusion detection system using fuzzy logic based on the particle swarm optimization algorithm: A case study(IOS Press, 2024-10-25)This paper presents an intelligent intrusion detection system using fuzzy logic based on particle swarm optimization algorithm. The main goal of this research is to survey the convergence capability of the particle swarm optimization algorithm using fuzzy logic in intelligent intrusion detection of a designable system. In order to simulate intelligent attacks on a system, KDD99 data are used. Based on the findings, the Particle Swarm Optimization (PSO) algorithm is highly capable of detecting an intelligent attack on a system. In this study, we considered 1800 times attack, in which the PSO algorithm was capable of repelling attacks in 7.24 seconds and converged. The best convergence occurred at stage 775, and then all attacks were eliminated from the system. Results showed that the stability and convergence of the system improved after each attack. Also, the number of attacks increased to 2500 times to investigate unpredictable intrusions and converge accrued at the attack 771st. Finally, the results obtained by the PSO algorithms were compared to the results obtained by the Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The findings indicate that the PSO algorithm is highly capable of detecting intelligent intrusions into a system. It is also suggested to employ this algorithm in cloud computing systems because of its high capability of repelling smart attacks.