Browsing by Author "Salas-Navarro K."

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An EPQ inventory model considering an imperfect production system with probabilistic demand and collaborative approach
(Emerald Group Publishing Ltd., 2019) Salas-Navarro K.; Acevedo Chedid, Jaime; Árquez G.M.; Florez W.F.; Ospina-Mateus H.; Sana S.S.; Cárdenas-Barrón L.E.
Purpose: The purpose of this paper is to propose an economic production quantity (EPQ) inventory model considering imperfect items and probabilistic demand for a two-echelon supply chain. The production process is imperfect and the imperfect quality items are removed from the lot size. The demand rate of the inventory system is random and follows an exponential probability density function and the demand of the retailers is depending on the initiatives of the sales team. Design/methodology/approach: Two approaches are examined. In the non-collaborative approach, any member of the supply chain can be the leader and takes decisions to optimize the profits, and in the collaborative system, all members make joint decisions about the production, supply, sales and inventory to optimize the profits of the supply chain members. The calculus approach is applied to find the maximum profit related to the members of the supply chain. Findings: A numerical example is presented to illustrate the performance of the EPQ model. The results show that collaborative approach generates greater profits to the supply chain and the market’s demand represents the variable behavior and uncertainty that is generated in the replenishment of a supply chain. Originality/value: The new and major contributions of this research are: the inventory model considers demand for products is random variable which follows an exponential probability distribution function and it also depends on the initiatives of sales teams, the imperfect production system generates defective items, different cycle time are considered in manufacturer and retailers and collaborative and non-collaborative approaches are also studied. © 2019, Emerald Publishing Limited.
Bibliometric analysis in motorcycle accident research: a global overview
(Springer Netherlands, 2019) Ospina-Mateus H.; Quintana Jiménez, Leonardo Augusto; López Valdés, Francisco J.; Salas-Navarro K.
770 million motorcycles are estimated on the roads. Motorcyclists represent more than 380,000 annual deaths worldwide. 28% of the global fatalities in the roads in 2016. With the increase of the accident rate, studies have been developed within the scientific literature. Bibliometric analysis is applied in the field of motorcycle safety in order to identify relevant publications on risk factors of road crashes and their implications. The information in this research was extracted from Web of Science and Scopus databases between 1947 and May 31, 2018. The study identified the key bibliometric indicators such as publications, authors, journals, countries, institutions, citation and co-citation analysis, subject categories, and co-occurrence of terms. EndNote, Microsoft Excel, Statgraphics Centurion and VOS-viewer software were used for the analysis. In total, 1813 articles were considered. The publications from 2000 to 2017 exhibits an average growth of 9%. The journal “Accident Analysis and Prevention” was the key issue in the publication and citation. The top institutions were the University of California, Universiti Putra Malaysia, and Monash University. The average citation of the top 10 articles was 134. A network visualization map showed that ‘vehicle’, ‘model’, ‘system’, ‘road’, ‘safety’, and ‘behavior’ were the most commons key terms. Bibliometric analysis demonstrates a high collaboration between authors and institutions. Two growing trends were identified. First, studies on the protection of the motorcyclist and the safe design considering the performance. Second, studies in analysis, characterization, and prevention of accidents. These studies are more related to the generation of strategies for the protection of road safety for motorcyclists. © 2019, Akadémiai Kiadó, Budapest, Hungary.
Model of optimization of mining complex for the planning of flow of quarry production of limestone in multiple products and with elements for the analysis of the capacity
(Springer Verlag, 2017) Ospina-Mateus H.; Acevedo Chedid, Jaime; Salas-Navarro K.; Morales-Londoño N.; Montero-Perez J.; Figueroa-Garcia J.C.; Lopez-Santana E.R.; Ferro-Escobar R.; Villa Ramírez, José Luis
Activities in mining complexes contain multiple decisions that affect the operations of the system for the extraction, transformation, transport and storage of various subsoil components. The purpose of this research is the planning of continuous flow production systems for mixed products, in non-metallic mining extraction processes, considering bottlenecks and capacity planning. This paper presents a model for production, based on mathematical optimization, that facilitates the planning and management of operations in the area of extraction, crushing and transformation of a quarry of aggregates for construction, considering the resources and the constraints that allow to define effective strategies in the increase of the productivity of the lines of low production environment by scenarios. This research develops an analysis of bottlenecks and contrasts the nature of the production system by means of a mathematical model of optimization, which considers the capacities and balances in the flows of the Limestone production line. The mathematical model that maximizes profits can be adapted to systems of continuous flow production in mining complexes where their products are part of a reverse logistics process, analysis of alternatives of extraction, transformation and transport. © 2017, Springer International Publishing AG.
Reactive scheduling in collaborative supply chain: A literature review
(Revista Espacios, 2017) Acevedo Chedid, Jaime; Salas-Navarro K.; Ospina-Mateus H.; Santander-Mercado A.
This paper aims to review the literature on the reprogramming of production in collaborative supply chains, through a thorough investigation and Scientometric analysis to identify the behavior of publications in recent years, which allow the identification of authors, areas Of the knowledge, countries and institutions most unrelated in the area. Finally, research lines are presented with a greater tendency for new research that contributes to the literature and the improvement of stocks. © 2017.
Using Data-Mining Techniques for the Prediction of the Severity of Road Crashes in Cartagena, Colombia
(Springer, 2019) Ospina-Mateus H.; Quintana Jiménez, Leonardo Augusto; López-Valdés F.J.; Morales-Londoño N.; Salas-Navarro K.; Figueroa-Garcia J.C.; Duarte-Gonzalez M.; Jaramillo-Isaza S.; Orjuela-Canon A.D.; Diaz-Gutierrez Y.
Objective: Analyze the road crashes in Cartagena (Colombia) and the factors associated with the collision and severity. The aim is to establish a set of rules for defining countermeasures to improve road safety. Methods: Data mining and machine learning techniques were used in 7894 traffic accidents from 2016 to 2017. The severity was determined between low (84%) and high (16%). Five classification algorithms to predict the accident severity were applied with WEKA Software (Waikato Environment for Knowledge Analysis). Including Decision Tree (DT-J48), Rule Induction (PART), Support Vector Machines (SVMs), Naïve Bayes (NB), and Multilayer Perceptron (MLP). The effectiveness of each algorithm was implemented using cross-validation with 10-fold. Decision rules were defined from the results of the different methods. Results: The methods applied are consistent and similar in the overall results of precision, accuracy, recall, and area under the ROC curve. Conclusions: 12 decision rules were defined based on the methods applied. The rules defined show motorcyclists, cyclists, including pedestrians, as the most vulnerable road users. Men and women motorcyclists between 20–39 years are prone in accidents with high severity. When a motorcycle or cyclist is not involved in the accident, the probable severity is low. © 2019, Springer Nature Switzerland AG.