A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives

This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestríaMagister en Ingeniería Industria

Simulation-optimization approach for the stochastic location-routing problem

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

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

4to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

Este volumen acoge la memoria académica de la Cuarta edición del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2017, desarrollado entre el 29 de noviembre y el 1 de diciembre de 2017 y organizado por la Universidad Politécnica Salesiana (UPS) en su sede de Guayaquil. El Congreso ofreció un espacio para la presentación, difusión e intercambio de importantes investigaciones nacionales e internacionales ante la comunidad universitaria que se dio cita en el encuentro. El uso de herramientas tecnológicas para la gestión de los trabajos de investigación como la plataforma Open Conference Systems y la web de presentación del Congreso http://citis.blog.ups.edu.ec/, hicieron de CITIS 2017 un verdadero referente entre los congresos que se desarrollaron en el país. La preocupación de nuestra Universidad, de presentar espacios que ayuden a generar nuevos y mejores cambios en la dimensión humana y social de nuestro entorno, hace que se persiga en cada edición del evento la presentación de trabajos con calidad creciente en cuanto a su producción científica. Quienes estuvimos al frente de la organización, dejamos plasmado en estas memorias académicas el intenso y prolífico trabajo de los días de realización del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad al alcance de todos y todas

The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery : a Benders decomposition approach

Crowd-shipping is an emergent solution to avoid the negative effects caused by the growing demand for last-mile delivery services. Previous research has studied crowd-shipping typically at an operational planning level. However, the study of support infrastructure within a city logistics framework has been neglected, especially from a strategic perspective. We investigate a crowd-sourced last-mile parcel delivery system supported by a network of strategically located mini-depots and present a two-stage stochastic network design problem with stochastic time-dependent arc capacity to fulfill stochastic express deliveries. The first-stage decision is the location of mini-depots used for decoupling flows allowing more flexibility for crowd–demand matching. The second stage of the problem is the demand allocation of crowd carriers or professional couriers for a finite set of scenarios. We propose an exact Benders decomposition algorithm embedded in a branch-and-cut framework. To enhance the algorithm, we use partial Benders decomposition, warm-start, and non-dominated cuts. We perform computational experiments on networks inspired by the public transportation network of Munich. The proposed solution method outperforms an off-the-shelf solver by solving instances 3.6 to 19 times faster. The results show the potential to exploit the stochastic crowd flows to deliver packages with deadlines of 3 or 8 h. The crowd can transport 8.3% to 32.5% of the total demand by using between 4% to 24% of the crowd capacity, and we observe average daily savings of 2.1% to 7.6% of the total expected operational cost. The results show values of the stochastic solution of at least 1% and up to 10%

FHC não pediu contrato de Mirian, diz firma

Jornalista afirma que Brasif usou contrato fictício para ajudar ex-presidente a enviar dinheiro para ela; tucano nega. Ministro da Justiça disse que área técnica de pasta está fazendo ‘estudo preliminar’ sobre declaraçõe

Computers & Industrial Engineering

En este documento, presentamos una encuesta de vanguardia sobre el problema de enrutamiento de vehículos con múltiples depósitos (MDVRP). Nuestra revisión consideró los artículos publicados entre 1988 y 2014, en los que se estudian varias variantes del modelo: ventanas de tiempo, entrega dividida, flota heterogénea, entregas periódicas y recolección y entrega. La revisión también clasifica los enfoques según los objetivos únicos o múltiples que están optimizados. También se presentan algunas líneas para futuras investigaciones.In this paper, we present a state-of-the-art survey on the vehicle routing problem with multiple depots (MDVRP). Our review considered papers published between 1988 and 2014, in which several variants of the model are studied: time windows, split delivery, heterogeneous fleet, periodic deliveries, and pickup and delivery. The review also classifies the approaches according to the single or multiple objectives that are optimized. Some lines for further research are presented as well

A literature review on the vehicle routing problem with multiple depots

15 páginasIn this paper, we present a state-of-the-art survey on the vehicle routing problem with multiple depots (MDVRP). Our review considered papers published between 1988 and 2014, in which several variants of the model are studied: time windows, split delivery, heterogeneous fleet, periodic deliveries, and pickup and delivery. The review also classifies the approaches according to the single or multiple objectives that are optimized. Some lines for further research are presented as well

Una revisión de la literatura sobre el problema de enrutamiento de vehículos con múltiples depósitos

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.El problema de enrutamiento de ubicación con el costo de transporte estocástico y las velocidades de viaje del vehículo es considerado en este trabajo. Se propone un procedimiento de solución híbrida basado en la optimización de colonias de Hormiga (ACO) y la simulación de eventos discretos (DES). Después de usar un algoritmo heurístico secuencial para resolver el sub-problema de ubicación, el problema de enrutamiento del vehículo capacitado posterior se resuelve utilizando ACO. Finalmente, un modelo DES evalúa esas rutas de vehículos en términos de su impacto en los costos totales esperados. El enfoque se prueba utilizando conjuntos de datos bien conocidos generados aleatoriamente. Dado que ningún trabajo previo en la literatura estudió exactamente el mismo SLRP, el procedimiento propuesto se compara con su versión determinista. Los resultados numéricos muestran la eficiencia y la eficacia del enfoque híbrido ACO-DES