Un algoritmo memético para el problema de localización-ruteo con ventanas de tiempo para la atención de desastres sísmicos: un caso de estudio de Bucaramanga, Colombia

Introduction: In recent years, a great part of the population has been affected by natural and man-caused disasters. Hence, evacuation planning has an important role in the reduction of the number of victims during a natural disaster. Objective: In order to contribute to current studies of operations research in disaster management, this paper addresses evacuation planning of urban areas by using buses to pick up affected people after an earthquake. Methodology: The situation is modeled using Location-Routing Problem with Time Windows (LRPTW) to locate emergency shelters and identify evacuation routes that meet attention time constraints. To solve the LRPTW problem, a memetic algorithm (MA) is designed to minimize the total response time during an evacuation. The algorithm is not only validated using instances of literature but also with the assessment of a case study of a seismic event in Bucaramanga, Colombia. Results and conclusions: The main contribution of this article is the development of a memetic algorithm for the solution of the proposed model that allows to solve real-size instances. The hybrid initialization of the MA prevents an early convergence by combining randomness and a heuristic technique. Computational results indicate that the MA is a viable approach for the LRPTW solution. Likewise, a case study is presented for the city of Bucaramanga in order to validate the proposed model. Two scenarios are simulated showing that the management of the time windows (homogeneous or random) directly influences the solution and affects the objective function. From a practical perspective, the location-routing problem must consider other criteria such as the cost of evacuation, including the attention delay cost, and the cost of opening shelters and routing.Introducción: En años recientes gran parte de la población ha sido afectada por desastres tanto naturales como antrópicos. Por esto, la planificación de la evacuación juega un papel importante en la reducción del número de víctimas ante un desastre natural. Objetivo: Con el propósito de contribuir a los estudios actuales desde la investigación de operaciones en gestión de desastres, esta investigación aborda la planificación de la evacuación de áreas urbanas usando buses para recoger afectados. Metodología: El problema se modela mediante un problema de localización-ruteo con ventanas de tiempo (LRPTW) para determinar el número y la ubicación de los albergues las y rutas de recolección para evacuación, cumpliendo restricciones en tiempo de atención. Para solucionar el LRPTW, se diseña un algoritmo memético (MA) que minimiza el tiempo total de respuesta en la evacuación. El algoritmo es validado en instancias de la literatura y mediante un caso de estudio de un evento sísmico en Bucaramanga (Colombia). Resultados y conclusiones: La contribución principal de este artículo es el desarrollo de un MA para solucionar el modelo propuesto, que permite resolver instancias de tamaño real. La inicialización híbrida del MA evita una convergencia temprana, combinando aleatoriedad con una técnica heurística. Los resultados computacionales indican que el MA es un enfoque viable para solucionar el LRPTW. Así mismo, se presenta un caso de estudio en Bucaramanga para validar el modelo propuesto. Se plantean dos escenarios de desastre, evidenciando que el tratamiento que se da a las ventanas de tiempo (homogénea o aleatoria) influye directamente en la solución y afecta la función objetivo. Desde un enfoque práctico, el problema debe considerar otros criterios que pueden influir en la planificación de la evacuación, como el costo de la evacuación, costo de la demora en la atención, costo de apertura y de ruteo

A memetic algorithm for location-routing problem with time windows for the attention of seismic disasters a case study from Bucaramanga, Colombia

Introduction− In recent years, a great part of the population has been affected by natural and man-caused disasters. Hence, evacua-tion planning has an important role in the reduction of the number of victims during a natural disaster. Objective−In order to contribute to current studies of operations research in disaster management, this paper addresses evacuation planning of urban areas by using buses to pick up affected people after an earthquake.Methodology−The situation is modeled using Location-Routing Problem with Time Windows (LRPTW) to locate emergency shelters and identify evacuation routes that meet attention time constraints. To solve the LRPTW problem, a memetic algorithm (MA) is de-signed to minimize the total response time during an evacuation. The algorithm is not only validated using instances of literature, but also with the assessment of a case study of a seismic event in Bucaramanga, Colombia.Results and conclusions− The main contribution of this article is the development of a memetic algorithm for the solution of the proposed model that allows to solve real-size instances. The hybrid initialization of the MA prevents an early convergence by combin-ing randomness and a heuristic technique. Computational results indicate that the MA is a viable approach for the LRPTW solution. Likewise, a case study is presented for the city of Bucaramanga in order to validate the proposed model. Two scenarios are simulated showing that the management of the time windows (homogeneous or random) directly influences the solution and affects the objec-tive function. From a practical perspective, the location-routing problem must consider other criteria such as the cost of evacua-tion, including the attention delay cost, and the cost of opening shelters and routing.Introducción− En años recientes gran parte de la población ha sido afectada por desastres tanto naturales como antrópicos. Por esto, la planificación de la evacuación juega un papel importante en la reduc-ción del número de víctimas ante un desastre natural. Objetivo− Con el propósito de contribuir a los estudios actuales desde la investigación de operaciones en gestión de desastres, esta inves-tigación aborda la planificación de la evacuación de áreas urbanas usando buses para recoger afectados.Metodología− El problema se modela mediante un problema de localización-ruteo con ventanas de tiempo (LRPTW) para determinar el número y la ubicación de los albergues las y rutas de recolección para evacuación, cumpliendo restricciones en tiempo de atención. Para solucionar el LRPTW, se diseña un algoritmo memético (MA) que minimiza el tiempo total de respuesta en la evacuación. El algo-ritmo es validado en instancias de la literatura y mediante un caso de estudio de un evento sísmico en Bucaramanga (Colombia).Resultados y conclusiones− La contribución principal de este ar-tículo es el desarrollo de un MA para solucionar el modelo propuesto, que permite resolver instancias de tamaño real. La inicialización híbrida del MA evita una convergencia temprana, combinando alea-toriedad con una técnica heurística. Los resultados computacionales indican que el MA es un enfoque viable para solucionar el LRPTW. Así mismo, se presenta un caso de estudio en Bucaramanga para validar el modelo propuesto. Se plantean dos escenarios de desastre, evidenciando que el tratamiento que se da a las ventanas de tiempo (homogénea o aleatoria) influye directamente en la solución y afec-ta la función objetivo. Desde un enfoque práctico, el problema debe considerar otros criterios que pueden influir en la planificación de la evacuación, como el costo de la evacuación, costo de la demora en la atención, costo de apertura y de ruteo

A memetic algorithm for location-routing problem with time windows for the attention of seismic disasters: a case study from Bucaramanga, Colombia

Introduction: In recent years, a great part of the population has been affected by natural and man-caused disasters. Hence, evacuation planning has an important role in the reduction of the number of victims during a natural disaster. Objective: In order to contribute to current studies of operations research in disaster management, this paper addresses evacuation planning of urban areas by using buses to pick up affected people after an earthquake. Methodology: The situation is modeled using Location-Routing Problem with Time Windows (LRPTW) to locate emergency shelters and identify evacuation routes that meet attention time constraints. To solve the LRPTW problem, a memetic algorithm (MA) is designed to minimize the total response time during an evacuation. The algorithm is not only validated using instances of literature but also with the assessment of a case study of a seismic event in Bucaramanga, Colombia. Results and conclusions: The main contribution of this article is the development of a memetic algorithm for the solution of the proposed model that allows to solve real-size instances. The hybrid initialization of the MA prevents an early convergence by combining randomness and a heuristic technique. Computational results indicate that the MA is a viable approach for the LRPTW solution. Likewise, a case study is presented for the city of Bucaramanga in order to validate the proposed model. Two scenarios are simulated showing that the management of the time windows (homogeneous or random) directly influences the solution and affects the objective function. From a practical perspective, the location-routing problem must consider other criteria such as the cost of evacuation, including the attention delay cost, and the cost of opening shelters and routing

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

A memetic algorithm for location-routing problem with time windows for the attention of seismic disasters: a case study from Bucaramanga, Colombia

Introduction: In recent years, a great part of the population has been affected by natural and man-caused disasters. Hence, evacuation planning has an important role in the reduction of the number of victims during a natural disaster.Objective: In order to contribute to current studies of operations research in disaster management, this paper addresses evacuation planning of urban areas by using buses to pick up affected people after an earthquake.Methodology: The situation is modeled using Location-Routing Problem with Time Windows (LRPTW) to locate emergency shelters and identify evacuation routes that meet attention time constraints. To solve the LRPTW problem, a memetic algorithm (MA) is designed to minimize the total response time during an evacuation. The algorithm is not only validated using instances of literature but also with the assessment of a case study of a seismic event in Bucaramanga, Colombia.Results and conclusions: The main contribution of this article is the development of a memetic algorithm for the solution of the proposed model that allows to solve real-size instances. The hybrid initialization of the MA prevents an early convergence by combining randomness and a heuristic technique. Computational results indicate that the MA is a viable approach for the LRPTW solution. Likewise, a case study is presented for the city of Bucaramanga in order to validate the proposed model. Two scenarios are simulated showing that the management of the time windows (homogeneous or random) directly influences the solution and affects the objective function. From a practical perspective, the location-routing problem must consider other criteria such as the cost of evacuation, including the attention delay cost, and the cost of opening shelters and routing.Introducción: En años recientes gran parte de la población ha sido afectada por desastres tanto naturales como antrópicos. Por esto, la planificación de la evacuación juega un papel importante en la reducción del número de víctimas ante un desastre natural.Objetivo: Con el propósito de contribuir a los estudios actuales desde la investigación de operaciones en gestión de desastres, esta investigación aborda la planificación de la evacuación de áreas urbanas usando buses para recoger afectados.Metodología: El problema se modela mediante un problema de localización-ruteo con ventanas de tiempo (LRPTW) para determinar el número y la ubicación de los albergues las y rutas de recolección para evacuación, cumpliendo restricciones en tiempo de atención. Para solucionar el LRPTW, se diseña un algoritmo memético (MA) que minimiza el tiempo total de respuesta en la evacuación. El algoritmo es validado en instancias de la literatura y mediante un caso de estudio de un evento sísmico en Bucaramanga (Colombia).Resultados y conclusiones: La contribución principal de este artículo es el desarrollo de un MA para solucionar el modelo propuesto, que permite resolver instancias de tamaño real. La inicialización híbrida del MA evita una convergencia temprana, combinando aleatoriedad con una técnica heurística. Los resultados computacionales indican que el MA es un enfoque viable para solucionar el LRPTW. Así mismo, se presenta un caso de estudio en Bucaramanga para validar el modelo propuesto. Se plantean dos escenarios de desastre, evidenciando que el tratamiento que se da a las ventanas de tiempo (homogénea o aleatoria) influye directamente en la solución y afecta la función objetivo. Desde un enfoque práctico, el problema debe considerar otros criterios que pueden influir en la planificación de la evacuación, como el costo de la evacuación, costo de la demora en la atención, costo de apertura y de ruteo