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A case of food supply chain management with AHP, DEMATEL, and TOPSIS

Ortiz Barrios, Miguel Angel; Miranda‐De la Hoz, Carlos; Meza López, Pedro; Petrillo, Antonella; De Felice, Fabio (Universidad de la Costa, 2019-08-27)

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, ...
A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand

Salas-Navarro, Katherinne; Acevedo-Chedid, Jaime; Florez, Whady F; Ospina Mateus, Holman; Cárdenas-Barrón, Leopoldo Eduardo; Sankar Sana, Shib (Corporación Universidad de la Costa, 2020)

This paper presents an inventory model for a three-echelon supply chain with multiple products and multiple members considering the demand as an increasing function of the marketing effort. In the proposed inventory model, ...
A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images

Escorcia-Gutierrez, Jose; Torrents-Barrena, Jordina; Gamarra, Margarita; Romero-Aroca, Pedro; Valls, Aida; Puig, Domenec (Corporación Universidad de la Costa, 2021-07-15)

Retinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural ...
A comparison study of MPC strategies based on minimum variance control index performance

BORRERO-SALAZAR, Alex A.; CARDENAS-CABRERA, Jorge M.; BARROS-GUTIERREZ, Daniel A.; JIMÉNEZ-CABAS, Javier A. (Espacios, 2019-07)

Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected ...
A complete psychophysiological profile of a paralympic athlete in a ultraendurance. a case study

Belinchon-De-Miguel, Pedro; Ruisoto, Pablo; Clemente Suárez, Vicente Javier (Association for Computing Machinery, 2018-10-24)

Psychophysiological response of athletes with spinal cord injurie has not been reported yet in scientific literature. The aim of this study is to analyze the specific psychophysiological response in a Paralympic athlete ...
A comprehensive study of biofilms growing on the built heritage of a caribbean industrial city in correlation with construction materials

Gallego Cartagena, Euler; MORILLAS, HECTOR; Maguregui, Maite; Patiño Camelo, Karen Lisana; Marcaida, Iker; MORGADO GAMERO, WENDY BEATRIZ; O. Silva, Luis F.; Madariaga, Juan Manuel (Universidad de la Costa, 2019)

Biodeteriogens growing on constructions belonging to the built heritage is one of the leading natural pathologies that cause aesthetical and in some cases, physical-geochemical problems in the materials. In this study, for ...
A computer simulation approach to reduce appointment lead-time in outpatient perinatology departments: a case study in a maternal-child hospital

Ortiz Barrios, M.; Jiménez Delgado, G.; De Ávila Villalobos, J. (Universidad De La Costa, 2017-06-25)

A significant problem in outpatient perinatology departments is the long waiting time for pregnant women to receive an appointment. In this respect, appointment delays are related to patient dissatisfaction, no shows and ...
A Cost Estimating Method for Agile Software Development

Aziz Butt, Shariq; Misra, Sanjay; Piñeres-Espitia, Gabriel; Ariza-Colpas, Paola; Mohan Sharma, Mayank (2021)

In every software development project, the software effort estimating procedure is an important process in software engineering and always critical. The consistency of effort and timeline estimation, along with several ...
A deep learning-based hybrid model for recommendation generation and ranking

Sivaramakrishnan, N.; Subramaniyaswamy, V.; amelec, viloria; Vijayakumar, V.; Senthilselvan, N. (2020)

A recommender system plays a vital role in information filtering and retrieval, and its application is omnipresent in many domains. There are some drawbacks such as the cold-start and the data sparsity problems which affect ...
A dispatching-fuzzy ahp-topsis model for scheduling flexible job-shop systems in industry 4.0 context

Ortíz-Barrios, Miguel; Petrillo, Antonella; De Felice, Fabio; Jaramillo-Rueda, Natalia; Jiménez-Delgado, Genett; Borrero-López, Luz (Corporación Universidad de la Costa, 2021-05-31)

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key ...
A FAHP-VIKOR approach for supporting the selection of tomography equipment in LMIC hospitals: a case study

Ortíz-Barrios, Miguel; Jaramillo-Rueda, Natalia; Petrillo, Antonella; Fernández-Mendoza, Zaury; Vidal-Pacheco, Lucelys (Corporación Universidad de la Costa, 2021)

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure ...
A fuzzy logic proposal for diagnosis multiple incipient faults in a power transformer

Fernández Blanco, Juan Carlos; Corrales Barrios, Luis Benigno; Hernández González, Félix Herminio; Benitez Pina, Israel Francisco; Núñez Alvarez, José Ricardo (Corporación Universidad de la Costa, 2021)

For the safety and continuity of service in industrial electrical systems, the availability of transformers is essential. For this reason, it is necessary to develop intelligent fault diagnosis techniques to reduce repair ...
A generic materials and operations planning approach for inventory turnover optimization in the chemical industry

Coronado-Hernández, Jairo R.; Romero-Conrado, Alfonso R.; Ochoa-González, Olmedo; Quintero-Arango, Humberto; Vargas, Ximena; Gatica, Gustavo (Corporación Universidad de la Costa, 2020)

Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming ...
A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry

Ortiz-Barrios, Miguel; Cabarcas Reyes, Juan Carlos; Ishizaka, Alessio; Barbati, Maria; Jaramillo-Rueda, Natalia; Carrascal-Zambrano, Giovani de Jesús (Corporación Universidad de la Costa, 2020-07-30)

Supplier selection has long been a strategic cornerstone for the advancement of companies from the mining sector due to its impact on many sectors as inventory management, production planning, maintenance scheduling, ...
A hybrid fuzzy multi-criteria decision-making model to evaluate the overall performance of public emergency departments: a case study

Ortiz Barrios, Miguel Angel; Alfaro-Saiz, Juan-Jose (Corporación Universidad de la Costa, 2020-10-05)

Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As di®erent criteria from ED context and several alternatives need to be considered, ...
A hydro pv hybrid system for the laranjeiras dam (in southern Brazil) operating with storage capacity in the water reservoir

Vasco, Gabriel; S. Silva, Jones; A. Canales, Fausto; Beluco, Alexandre; de Souza, José; G. Rossini, Elton (Smart Grid and Renewable Energy, 2019-04-28)

Seasonal variability coupled with the intermittency of renewable energy sources makes reservoir hydroelectric plants an interesting option to consider in hybrid energy systems, especially in cases of dams that have not ...
A laboratory approach to measure enhanced gas recovery from a tight gas reservoir during supercritical carbon dioxide injection

Syah, Rahmad; Mehdi Alizadeh, Seyed; Nurgalieva, Karina; Grimaldo Guerrero, John William; Nasution, Mahyuddin K. M.; Davarpanah, Afshin; Ramdan, Dadan; Metwally, Ahmed S. M. (Corporación Universidad de la Costa, 2021-09-20)

Supercritical carbon dioxide injection in tight reservoirs is an efficient and prominent enhanced gas recovery method, as it can be more mobilized in low-permeable reservoirs due to its molecular size. This paper aimed to ...
A learners experience with the games education in software engineering

Tariq, Muhammad Imran; Diaz-Martinez, Jorge; aziz, shariq; Javaid, Adeel; De-La-Hoz-Franco, Emiro; Mihaela Dicu, Anca (Corporación Universidad de la Costa, 2020)

The utilization of games and its components in software building training isn’t new. In reality, their usage in Software development training is found to look into papers for numerous decades. Be that as it may, there is ...
A literature review on the vehicle routing problem with multiple depots

Montoya Torres, Jairo R.; López Franco, Julián; Nieto Isaza, Santiago; Felizzola Jiménez, Heriberto; Herazo Padilla, Nilson Sebastian (Universidad de la Costa, 2015-02-15)

The location routing problem with stochastic transportation cost and vehicle travel speeds is considered in this paper. A hybrid solution procedure based on Ant Colony Optimisation (ACO) and Discrete-Event Simulation (DES) ...
A look to the Electricity Generation from Non-Conventional Renewable Energy Sources in Colombia

Cabello Eras, Juan Jose; Balbis Morejón, Milen; Sagastume Gutiérrez, Alexis; Pardo García, Aldo; Cabello Ulloa, Mario Javier; Rey Martínez, Francisco Javier; Rueda Bayona, Juan Gabriel (International Journal of Energy Economics and PolicyUniversidad de la Costa, 2019-11-28)

This study discusses the potentialities and current situation of the electricity generation from non-conventional renewable energy sources (NCRES) in Colombia. In particular, three scenarios considering the increment of ...

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A case of food supply chain management with AHP, DEMATEL, and TOPSIS
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Ortiz Barrios, Miguel Angel | 2019-08-27

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, it is necessary, apart from other interventions, to continuously monitor the performance of food suppliers so that the demand information flow, order batching, transportation planning, and inventory management can be substantially improved. Therefore, supplier assessment has then become critical decision‐making support for identifying and addressing inefficiencies of food providers, which ends up reducing the variation of several key logistics parameters for upstream members of the food supply chain. In addition, such assessment is of multicriteria nature given the presence of several criteria from different domains and various food suppliers. With these considerations in mind, this paper proposes a hybrid approach integrating the analytic hierarchy process (AHP), decision‐making trial and evaluation laboratory (DEMATEL), and the technique for order of preference by similarity to ideal solution (TOPSIS) for evaluating the performance of pork suppliers. Thereby, the economic and operational burden caused by the bullwhip effect throughout the pork supply chain can be alleviated. AHP was first used to determine the criteria and subcriteria weights. Then DEMATEL was applied to assess the interdependence and feedback between the decision elements. Finally, TOPSIS was implemented to discriminate between high‐performance and low‐performance pork suppliers. A case study from the Colombian pork supply chain is presented to validate the proposed approach. The results of this study evidenced that the most important criterion was the “service level” and the most influencing factor was the “financial profile.” In addition, based on the supplier assessment results, improvement plans, and new negotiation, strategies were established for each supplier in order to diminish the bullwhip effect along the pork supply chain.

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A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand
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Salas-Navarro, Katherinne | 2020

This paper presents an inventory model for a three-echelon supply chain with multiple products and multiple members considering the demand as an increasing function of the marketing effort. In the proposed inventory model, a collaborative approach is studied and an analytical method is applied to obtain the optimal production lot size and the optimal marketing effort in order to achieve the maximum profits. Some numerical examples are illustrated to justify the model. Moreover, a sensitivity analysis is well done in order to analysis the effect of the changes of key parameters of inventory model on the the maximum benefits of all members of the chain.

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A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images
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Escorcia-Gutierrez, Jose | 2021-07-15

Retinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural components in color fundus images like the optic disc (OD) is crucial to diagnose retinal diseases. Automatic OD detection is complex because of its location in an area where blood vessels converge, and color distribution is uneven. Several image processing techniques have been developed for OD detection so far, but vessel segmentation is sometimes required, increasing computational complexity and time. Moreover, precise OD segmentation methods utilize complex algorithms that need special hardware or extensive labeled datasets. We propose an OD detection approach based on the Modern Portfolio Theory of Markowitz to generate an innovative color fusion model. Specifically, the training phase calculates the optimal weights for each color channel. A fusion of weighted color channels is then applied in the testing phase. This approach acts as a powerful and real-time preprocessing stage. We use four heterogeneous datasets to validate the presented methodology. Three out of four datasets are publicly available (i.e., DRIVE, Messidor, and HRF), and the last corresponds to an in–house dataset acquired from Hospital Universitari Sant Joan de Reus (Spain). Two different segmentation methods are presented and compared with state-of-the-art computer vision techniques to analyze the model performance. An outstanding accuracy and overlap above 0.9 and 80%, respectively, and a minimal execution time of 0.05 s are reached. Therefore, our model could be integrated into daily clinical practice to accelerate the diagnosis of Diabetic Retinopathy due to its simplicity, performance, and speed.

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A comparison study of MPC strategies based on minimum variance control index performance
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BORRERO-SALAZAR, Alex A. | 2019-07

Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected to control process variables directly. The strategies studied are IMC, GPC, MPC-D, MPC-DR, and DMC. Evaluation of the performance of the controlled loop was performed with the filtering and correlation analysis algorithm (FCOR). The methodology proposed is validated in a Continuous Stirred-Tank Reactor (CSTR) case study. Discrete predictive control demonstrated the best results in this study.

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A complete psychophysiological profile of a paralympic athlete in a ultraendurance. a case study
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Belinchon-De-Miguel, Pedro | 2018-10-24

Psychophysiological response of athletes with spinal cord injurie has not been reported yet in scientific literature. The aim of this study is to analyze the specific psychophysiological response in a Paralympic athlete during competitive activities. We collected the following psychophysiological measurements: anxiety-trait, anxiety-state, locus of control, perceived psychological stress, stress-copying style, rate of perceived exertion, perceived muscle pain, body temperature, forced vital capacity, blood oxygen saturation, blood glucose and lactate concentrations, isometric hand strength, cortical arousal, heart rate variability, heart rate and velocities of a female Paralympic spinal cord injured athlete in a 11 hours and 44 minutes mountain ultraendurance event. An increase in sympathetic autonomous nervous system, heart rate, lactate, muscular pain and rated of perceived exertion and a decrease in cortical arousal and hand strength and inspiratory muscle fatigue. These results are consistent with the expected response during a highly stressful situation and consistent with previous findings in athletes without spinal cord injurie.

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A comprehensive study of biofilms growing on the built heritage of a caribbean industrial city in correlation with construction materials
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Gallego Cartagena, Euler | 2019

Biodeteriogens growing on constructions belonging to the built heritage is one of the leading natural pathologies that cause aesthetical and in some cases, physical-geochemical problems in the materials. In this study, for the first time, the chemical composition of construction materials of the built heritage from an industrialized city (Barranquilla) of Colombia have been evaluated in correlation with the algal, cyanobacterial and fungal biodeteriogens present in biofilms by applying a multianalytical methodology. To achieve this objective, samples of biofilms and construction material were taken from different historical and modern constructions. For the mineralogical characterization of the construction materials, X-ray diffraction, Raman microscopy and energy dispersive X-ray fluorescence spectrometry (EDXRF) were used. In addition, microscopic observations and cultures were employed for the microbiological characterization. Most of the construction materials analyzed belong to calcareous mortars, and others to different types of cement (portlandite, ettringite and larnite identification). The EDXRF analysis through single point and imaging strategies allowed to identify differences in the elemental composition of the external and internal parts of the materials. The role of certain elements in the mortars, which will assist the growth of specific microorganisms, is also discussed in this work. The main biodeteriogens identified in the biofilms were cyanobacteria Oscillatoria sp., Lyngbya sp., Leptolyngbya sp. and Ascomycota Aspergillus niger, Aspergillus fumigatus, Penicillium sp. and Fusarium sp fungi. These microorganisms promote biodeterioration processes causing aesthetic, physical and chemical damage to the façades of the studied buildings. The mineralogical composition of the construction material together with environmental conditions contributes to the development of biofilms on the constructions and monuments of Barranquilla city. The results obtained in this study will be used in the future to design and implement conservation protocols and strategies useful to preserve the built heritage of Caribbean cities with similar climate conditions, geographical position and kind of construction materials

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A computer simulation approach to reduce appointment lead-time in outpatient perinatology departments: a case study in a maternal-child hospital
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Ortiz Barrios, M. | 2017-06-25

A significant problem in outpatient perinatology departments is the long waiting time for pregnant women to receive an appointment. In this respect, appointment delays are related to patient dissatisfaction, no shows and sudden infant death syndrome. This paper aims to model and evaluate improvement proposals to outpatient care delivery by applying computer simulation approaches. First, suitable data is collected and analyzed. Then, a discrete-event simulation (DES) model is created and validated to determine whether it is statistically equivalent to the current system. Afterward, the average appointment lead-time is calculated and studied. Finally, improvement proposals are designed and pretested by simulation modelling and statistical comparison tests. A case study of an outpatient perinatology department from a maternal-child is shown to validate the effectiveness of DES to fully understand and manage healthcare systems. The results evidenced that changes to care delivery can be effectively assessed and appointment lead-times may be significantly reduced based on the proposed framework within this paper.

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A Cost Estimating Method for Agile Software Development
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Aziz Butt, Shariq | 2021

In every software development project, the software effort estimating procedure is an important process in software engineering and always critical. The consistency of effort and timeline estimation, along with several factors, determines whether a project succeeds or fails. Both academics and professionals worked on the estimation approaches in software engineering. But, all these approaches have many problems that need to be addressed. One of the most difficult aspects of software engineering is estimating effort in agile development. This study aims to provide an effort estimation method for agile software development projects. Because in software engineering, the agile method is widely used for the development of software applications. The development and usage of the agile method are described in depth in this study. The framework is configured with empirical data gathered by projects from the software industry. The test findings reveal that the estimation method has great estimation accuracy in respect of mean magnitude of relative error (MMRE) and Prediction of Error PRED (n). The suggested approach achieves more accuracy for effort estimation as compare to others.

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A deep learning-based hybrid model for recommendation generation and ranking
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Sivaramakrishnan, N. | 2020

A recommender system plays a vital role in information filtering and retrieval, and its application is omnipresent in many domains. There are some drawbacks such as the cold-start and the data sparsity problems which affect the performance of the recommender model. Various studies help with drastically improving the performance of recommender systems via unique methods, such as the traditional way of performing matrix factorization (MF) and also applying deep learning (DL) techniques in recent years. By using DL in the recommender system, we can overcome the difficulties of collaborative filtering. DL now focuses mainly on modeling content descriptions, but those models ignore the main factor of user–item interaction. In the proposed hybrid Bayesian stacked auto-denoising encoder (HBSADE) model, it recognizes the latent interests of the user and analyzes contextual reviews that are performed through the MF method. The objective of the model is to identify the user’s point of interest, recommending products/services based on the user’s latent interests. The proposed two-stage novel hybrid deep learning-based collaborative filtering method explores the user’s point of interest, captures the communications between items and users and provides better recommendations in a personalized way. We used a multilayer neural network to manipulate the nonlinearities between the user and item communication from data. Experiments were to prove that our HBSADE outperforms existing methodologies over Amazon-b and Book-Crossing datasets.

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A dispatching-fuzzy ahp-topsis model for scheduling flexible job-shop systems in industry 4.0 context
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Ortíz-Barrios, Miguel | 2021-05-31

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery. View Full-Text

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A FAHP-VIKOR approach for supporting the selection of tomography equipment in LMIC hospitals: a case study
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Ortíz-Barrios, Miguel | 2021

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure of the skeleton, tissues, and organs. However, the appropriate CT-SCAN selection is an arduous task considering the complexity and high cost of these medical devices. This decision is even more sharpener in hospitals from Low-and-Middle-Income-Countries (LMIC) where the available budget is usually restricted and correct resource allocation should be therefore ensured while granting the greatest impact on the timeliness and efficacy of healthcare services. In this framework, multiple criteria from diverse fields need to be taken into account to satisfy the intricate requirements of users. In this regard, it is necessary to fully elicit the expectations of stakeholders as well as identify their importance in an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall appropriateness index per CT-SCAN candidate and thereby identifying the most pertinent one (s) for a specific LMIC medical institution. © 2021, Springer Nature Switzerland AG.

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A fuzzy logic proposal for diagnosis multiple incipient faults in a power transformer
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Fernández Blanco, Juan Carlos | 2021

For the safety and continuity of service in industrial electrical systems, the availability of transformers is essential. For this reason, it is necessary to develop intelligent fault diagnosis techniques to reduce repair and maintenance costs. Recently, several methods have been developed that use artificial intelligence techniques such as neural networks, support vector machines, hybrid techniques, etc., for the diagnosis of faults in power transformers using gas analysis. These methods, although they present very good results, encounter restrictions to determine the precise moment before the occurrence of multiple fault of small magnitude and are difficult to implement in practice. This document proposes a method to diagnose multiple incipient faults in a power transformer using fuzzy logic. The proposal, based on historical data from the composition of the gases dissolved in the oil, achieves a performance in the classification of multiple incipient fault of 98.3%. With reliable samples of dissolved gas, it guarantees an overall rate of accuracy in detecting incipient faults that is superior to that obtained by the most successful conventional methods in the industry. The proposal does not encounter generalization difficulties and constitutes a simple solution that allows determining the state of the transformer in service without affecting the continuity of the electricity supply.

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A generic materials and operations planning approach for inventory turnover optimization in the chemical industry
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Coronado-Hernández, Jairo R. | 2020

Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming model (MIP) based on the Generic Materials and Operations Planning Problem (GMOP) for optimizing the inventory turnover in a fertilizer company. Results showed significant improvements for Inventory Turnover Ratios and overall costs when compared with an empirical production planning method.

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A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry
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Ortiz-Barrios, Miguel | 2020-07-30

Supplier selection has long been a strategic cornerstone for the advancement of companies from the mining sector due to its impact on many sectors as inventory management, production planning, maintenance scheduling, financial resources and environment. In this regard, expert decision-makers should deem a number of performance conflicting criteria and supplier alternatives. Moreover, choosing a suitable Multi-Criteria Decision Making (MCDM) approach has become a key strategic consideration for supplier selection. Hence, this paper presents a combination of powerful MCDM methods to select the most suitable supplier of forklift filters. The Fuzzy Analytic Hierarchy Process (FAHP) is first used to calculate the initial weights of criteria and sub-criteria under uncertainty, followed by the implementation of Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) to assess the interrelations and feedback between them. The fuzzy theory is used in both AHP and DEMATEL methods to represent the human vagueness when making judgments. Then, FAHP and FDEMATEL are combined to obtain the final contributions of both criteria and sub-criteria on the basis of interrelations and uncertainty. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank the supplier alternatives. To validate the effectiveness of the proposed framework, a case study is presented. The results evidence that quality criterion is the most crucial aspect when selecting suppliers of forklift filters.

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A hybrid fuzzy multi-criteria decision-making model to evaluate the overall performance of public emergency departments: a case study
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Ortiz Barrios, Miguel Angel | 2020-10-05

Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As di®erent criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address this challenge, a more complete approach is still lacking. This paper bridges this gap by integrating three potent MCDM methods. First, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the criteria and sub-criteria weights under uncertainty, followed by the interdependence evaluation via fuzzy DecisionMaking Trial and Evaluation Laboratory (FDEMATEL). The fuzzy logic is merged with AHP and DEMATEL to illustrate vague judgments. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking EDs. This approach is validated in a real 3-ED cluster. The results revealed the critical role of Infrastructure (21.5%) in ED performance and the interactive nature of Patient safety (C þ R ¼ 12:771). Furthermore, this paper evidences the weaknesses to be tackled for upgrading the performance of each ED.

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A hydro pv hybrid system for the laranjeiras dam (in southern Brazil) operating with storage capacity in the water reservoir
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Vasco, Gabriel | 2019-04-28

Seasonal variability coupled with the intermittency of renewable energy sources makes reservoir hydroelectric plants an interesting option to consider in hybrid energy systems, especially in cases of dams that have not been completed or have been abandoned and which still have some potential for reuse. The Laranjeiras dam was completed in the 1960s and the original project for hydroelectric power generation was not completed, made impossible by economic changes during the construction years. A recent study proposed the implementation of a hydroelectric photovoltaic hybrid system with lower horsepower to allow the dam to be made useful again. This paper presents the results of the computational simulations with the software Homer, considering the operation of the hydroelectric component (of the proposed hybrid system) with reservoir, playing the role of energy storage device when the production exceeds the demand at a given moment, reducing the loss of energy due to unavailability of demand. The study suggested to implement a hydroelectric power plant with power house at the base of the dam that has a height of 20 m, operating at a minimum flow of 9171 L/s, with reservoir operating as a device for energy storage, operating with a photovoltaic system of 360 kW, and a power limit for the purchase of energy from the grid equal to 200 kW, providing consumer loads up to 40 MWh per day, with cost of energy equal to US$0.021 per kWh and a capital cost of US$3285.617.

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A laboratory approach to measure enhanced gas recovery from a tight gas reservoir during supercritical carbon dioxide injection
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Syah, Rahmad | 2021-09-20

Supercritical carbon dioxide injection in tight reservoirs is an efficient and prominent enhanced gas recovery method, as it can be more mobilized in low-permeable reservoirs due to its molecular size. This paper aimed to perform a set of laboratory experiments to evaluate the impacts of permeability and water saturation on enhanced gas recovery, carbon dioxide storage capacity, and carbon dioxide content during supercritical carbon dioxide injection. It is observed that supercritical carbon dioxide provides a higher gas recovery increase after the gas depletion drive mechanism is carried out in low permeable core samples. This corresponds to the feasible mobilization of the supercritical carbon dioxide phase through smaller pores. The maximum gas recovery increase for core samples with 0.1 mD is about 22.5%, while gas recovery increase has lower values with the increase in permeability. It is about 19.8%, 15.3%, 12.1%, and 10.9% for core samples with 0.22, 0.36, 0.54, and 0.78 mD permeability, respectively. Moreover, higher water saturations would be a crucial factor in the gas recovery enhancement, especially in the final pore volume injection, as it can increase the supercritical carbon dioxide dissolving in water, leading to more displacement efficiency. The minimum carbon dioxide storage for 0.1 mD core samples is about 50%, while it is about 38% for tight core samples with the permeability of 0.78 mD. By decreasing water saturation from 0.65 to 0.15, less volume of supercritical carbon dioxide is involved in water, and therefore, carbon dioxide storage capacity increases. This is indicative of a proper gas displacement front in lower water saturation and higher gas recovery factor. The findings of this study can help for a better understanding of the gas production mechanism and crucial parameters that affect gas recovery from tight reservoirs.

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A learners experience with the games education in software engineering
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Tariq, Muhammad Imran | 2020

The utilization of games and its components in software building training isn’t new. In reality, their usage in Software development training is found to look into papers for numerous decades. Be that as it may, there is little data about the real reception of these methodologies in games designing and development training in terms of software building. Consequently, the objective of this paper is to research the utilization of game’s components in programming designing instruction, in the viewpoint of teachers. To accomplish this objective, this examination proposes and breaks down the aftereffects of a study replied by numerous product designing teachers. We test the members by welcoming multiple instructors from settled colleges and instructive organizations of various districts. The first objective of the review is to gather data relates to the utilization of important games and rich gamification in the student classrooms, and the second objective is to comprehend information territories and the pre-owned game-related techniques. The outcomes show that the more significant part of the educators knows about these instructive methodologies, the games were embraced by various members. Games that are generally played to cover “Programming Process” & “Task Management.” The utmost utilized game apparatuses are Points scoring, Quizzes solving, and meet challenges. The outcomes additionally reveal that the fundamental explanations behind not embracing the assets are the absence of information, lack of data about essential games for encouraging programming designing, and the absence of time to design and remember these methodologies for the classes At long last, results show a definite propensity towards the future appropriation of these game-related methodologies by the product developing teachers.

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A literature review on the vehicle routing problem with multiple depots
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Montoya Torres, Jairo R. | 2015-02-15

The location routing problem with stochastic transportation cost and vehicle travel speeds is considered in this paper. A hybrid solution procedure based on Ant Colony Optimisation (ACO) and Discrete-Event Simulation (DES) is proposed. After using a sequential heuristic algorithm to solve the location subproblem, the subsequent capacitated vehicle routing problem is solved using ACO. Finally, a DES model evaluates those vehicle routes in terms of their impact on the expected total costs. The approach is tested using well-known randomly generated datasets. Since no previous works in the literature studied exactly the same SLRP, the proposed procedure is compared against its deterministic version. Numerical results show the efficiency and efficacy of the hybrid ACO-DES approach.

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A look to the Electricity Generation from Non-Conventional Renewable Energy Sources in Colombia
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Cabello Eras, Juan Jose | 2019-11-28

This study discusses the potentialities and current situation of the electricity generation from non-conventional renewable energy sources (NCRES) in Colombia. In particular, three scenarios considering the increment of NCRES electricity based generation installed capacity are discussed. The three scenarios are compared to the 2020 forecast of the Energy and Mining Planning Unit ((UPME). Overall, it id shown that Colombia has a significant unused NCRES potential, which makes possible to realize the 6% target for NCRE based electricity generation capacity installed by 2020. In particular, the photovoltaic energy is foresee to account for over half of the NCRE mix. Even though the law 1715 is a progress towards integrating NCRE to the National Electric System, more policies and developments are required, to further the NCRE based installed generation capacities.

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