Modelo para el problema de localización y ruteo de vehículos con ventanas de tiempo en Bogotá usando flota heterogénea

Este trabajo estudia el problema de localización de planta y ruteo de vehículos con flota heterogénea y ventanas de tiempo en Bogotá. Para ello se diseñó un modelo meta heurístico comparando las posibles implicaciones asociadas a la ubicación de una instalación en áreas industriales de la ciudad, frente a su ubicación en áreas aledañas como Funza, Mosquera, Tocancipá, asumiendo los costos de ubicación y transporte hacia el interior. Los costos de ubicación de plantas en áreas industriales en Bogotá son mayores a los costos de tierra en municipios cercanos, los cuales cuentan con la facilidad de acceso a carreteras nacionales que garantizan la cobertura a clientes y acceso a proveedores. Tal como mencionan (Rincon-Garcia, Waterson, & Cherrett, 2017)), actualmente la industria se enfrenta a desafíos en temas de transporte, entre ellos, la congestión vial, las regulaciones distritales y los requerimientos por parte de los clientes en cuanto al cumplimiento de entregas en ventanas de tiempo estrechas. Dicho lo anterior, es oportuno desarrollar un modelo que soporte la toma de decisiones en el problema de locación y transporte en Bogotá, teniendo en cuenta las zonas y horarios delimitados para el tránsito de los diferentes vehículos de carga; siendo esta una de las principales restricciones al momento de definir rutas de distribución.This paper studies the facility location and vehicle routing problem with heterogeneous fleet and time windows in Bogotá. For this purpose, we designed a meta heuristic model to compare the implications of locating a facility in the city or the close villages like Funza, Mosquera, Tocancipá, assuming the location and transport costs to the inside. The facility location costs in Bogotá are superior in terms of land price, which have access to national roads assuring customer covering and easy access to suppliers. As mentioned by Rincon-Garcia et al, the industry currently faces challenges in distribution, among them, traffic jam, district regulations, and customers' requirements, delivery fulfillment in narrow time windows. With this in mind is opportune to develop a model that supports the decision taking in the location and routing problem in Bogotá, considering the zones and schedules existing for the cargo vehicle's transit; with this one being the principal constraints at the moment of define a route. Taking into account that this problem is an extension of the VRPTW problem, of NP-Hard complexity, we'll use meta heuristic models oriented to minimize costs, instead of exact method since they have not demonstrated optimal solutions for instances with more than 100 nodes.Ingeniero (a) IndustrialPregrad

Physical internet-enabled hyperconnected distribution assessment

L'Internet Physique (IP) est une initiative qui identifie plusieurs symptômes d'inefficacité et non-durabilité des systèmes logistiques et les traite en proposant un nouveau paradigme appelé logistique hyperconnectée. Semblable à l'Internet Digital, qui relie des milliers de réseaux d'ordinateurs personnels et locaux, IP permettra de relier les systèmes logistiques fragmentés actuels. Le but principal étant d'améliorer la performance des systèmes logistiques des points de vue économique, environnemental et social. Se concentrant spécifiquement sur les systèmes de distribution, cette thèse remet en question l'ordre de magnitude du gain de performances en exploitant la distribution hyperconnectée habilitée par IP. Elle concerne également la caractérisation de la planification de la distribution hyperconnectée. Pour répondre à la première question, une approche de la recherche exploratoire basée sur la modélisation de l'optimisation est appliquée, où les systèmes de distribution actuels et potentiels sont modélisés. Ensuite, un ensemble d'échantillons d'affaires réalistes sont créé, et leurs performances économique et environnementale sont évaluées en ciblant de multiples performances sociales. Un cadre conceptuel de planification, incluant la modélisation mathématique est proposé pour l’aide à la prise de décision dans des systèmes de distribution hyperconnectée. Partant des résultats obtenus par notre étude, nous avons démontré qu’un gain substantiel peut être obtenu en migrant vers la distribution hyperconnectée. Nous avons également démontré que l'ampleur du gain varie en fonction des caractéristiques des activités et des performances sociales ciblées. Puisque l'Internet physique est un sujet nouveau, le Chapitre 1 présente brièvement l’IP et hyper connectivité. Le Chapitre 2 discute les fondements, l'objectif et la méthodologie de la recherche. Les défis relevés au cours de cette recherche sont décrits et le type de contributions visés est mis en évidence. Le Chapitre 3 présente les modèles d'optimisation. Influencés par les caractéristiques des systèmes de distribution actuels et potentiels, trois modèles fondés sur le système de distribution sont développés. Chapitre 4 traite la caractérisation des échantillons d’affaires ainsi que la modélisation et le calibrage des paramètres employés dans les modèles. Les résultats de la recherche exploratoire sont présentés au Chapitre 5. Le Chapitre 6 décrit le cadre conceptuel de planification de la distribution hyperconnectée. Le chapitre 7 résume le contenu de la thèse et met en évidence les contributions principales. En outre, il identifie les limites de la recherche et les avenues potentielles de recherches futures.The Physical Internet (PI) is an initiative that identifies several symptoms of logistics systems unsustainability and inefficiency and tackles them by proposing a novel paradigm called Hyperconnected Logistics. Similar to the Digital Internet, which connects thousands of personal and local computer networks, PI will connect the fragmented logistics systems of today. The main purpose is to enhance the performance of logistics systems from economic, environmental and social perspectives. Focusing specifically on the distribution system, this thesis questions the order of magnitude of the performance gain by exploiting the PI-enabled hyperconnected distribution. It is also concerned by the characterization of the hyperconnected distribution planning. To address the first question, an exploratory research approach based on optimization modeling is applied; first, the current and prospective distribution systems are modeled. Then, a set of realistic business samples are created, and their economic and environmental performance by targeting multiple social performances are assessed. A conceptual planning framework is proposed to support the decision making in the hyperconnected distribution system. Based on the results obtained by our investigation, it can be argued that a substantial gain can be achieved by shifting toward Hyperconnected Distribution. It is also revealed that the magnitude of the gain varies by business characteristics and the targeted social performance. Since the Physical Internet is a novel topic, chapter 1 briefly introduces PI and Hyperconnected Logistics. Chapter 2 discusses the research foundations, goal and methodology. It also describes the challenges of conducting this research and highlights the type of contributions aimed for. Chapter 3 presents the optimization models including a core distribution network design modeling approach. Influenced by the characteristics of the current and prospective distribution systems, three distribution system-driven models are developed. Chapter 4 engages with the characterization of the business samples, the modeling and calibration of the parameter that are employed in the models. The exploratory investigation results are presented in Chapter 5. Chapter 6 describes the hyperconnected distribution planning framework. Chapter 7 summarizes the content of the thesis and highlights the main contributions. Moreover, it identifies the research limitations and potential future research avenues

An integrated framework for improving supply chain performance

In 2009, Roland Berger Strategy Consultants [Roland Berger Strategy Consultants, (2009). Global SCM excellence study., p.5.] reported that 40% of 234 companies had the wrong priorities in regard to efficiency vs. responsiveness. In 2014, PricewaterhouseCoopers (PwC) and American Production and Inventory Control Society (APICS) [PwC and APICS, Sustainable supply chains: Making value the priority 2014] found that 76% of 500 supply chain executives identified sustainability as an important aspect of their supply chain. The results highlight the importance of achieving consistency between customer expectations, in terms of cost and service level, and supply chain performance in today’s competitive business environment. Despite this, however, no integrated supply chain design framework exists to control majority of the important functions related to supply chain strategy, structure, process and performance. The literature review showed that simulation is rarely considered at the strategic level, but the research experiments highlighted a number of ways in which simulation tools might be useful at this level, such as exploring the impact of strategic fit and decoupling points, and assessing different supply chain network configurations and policies. This research contributes to knowledge by designing and developing a framework that integrates strategy, process and resources, and allows the use of simulation tools to consider the three dimensions of efficiency, responsiveness and sustainability concurrently during the design process. The proposed framework is validated using a hypothetical supply chain network. Simulation allows performance to be assessed under a range of scenarios. The simulation experiments showed that under the suggested policies, efficiency improved from 25.38% to 30.58% and responsiveness rose from 18.37% to 32.78%. However, they also indicated that while policies oriented towards improving responsiveness had a positive impact on sustainability, those oriented towards improving efficiency had a negative impact. The significance of the research lies in its development of a supply chain design framework that could assist companies in achieving the optimum configuration of supply chain resources, thereby helping them reduce inventory, lower costs, enhance responsiveness and improve strategic focus in terms of design, execution and capital investments

Valoración del riesgo en un modelo multinivel de suministro

Risk management is a structured approach that incorporates uncertainty related to a threat, linked to a sequence of inherently human activities that include risk assessment, as well as other strategies for its mitigation. The objective is to reduce different risks related to a pre-selected area. Your classification it is diverse, for example: threats due to factors associated with the environment, technology, human errors, organizations, among others. The risk assessment is being consolidated as a support tool for the analysis of decisions under conditions of uncertainty, particularly for complex systems, such as supply chains. Without a doubt, risk management. It becomes relevant being a critical component in management decisions, as it is a continuous process. From this perspective, Through parametric approaches and multivariate analysis, it has been possible to study and represent the resulting data to observe more than one statistical variable on a particular population. For which an instrument has been designed and validated for the collection of information through the configuration of an interface on-line. We have oriented our efforts to know what is the perception of risk, the strategies of collaboration, as well as as the identification of logistic practices, given a conglomerate of actors, particularly in risk contexts associated with hydrometeorological phenomena. In a second instance, based on the previous steps, we have proposed modeling and the simulation approach of Monte Carlo to identify the impact of competitive risks. This paradigm has been consolidated in medical science, but nowadays you can find contributions in the social sciences, engineering, acting, among others. Our approach proposes a selection of causes of failure belonging to a set of possible events, which were identified in the diagnostic phase. We specify the modeling through the identification and discrimination of risks for each level of supply. Through the simulation of competitive risks, the cumulative incidence, the probabilities of occurrence and the compliance rates for a multilevel supply model. Also, an alternative and versatile solution was formulated for diversify the instruments, methods and techniques of risk treatment in supply chains. The solution, estimates the probability of failure for a given cause, before the specific expiration time. Finally, a case study was proposed where, through the simulation approach, the behavior of a set of instances, whose analysis component is subject in particular to sudden disruptions of supplies,associated with hydrometeorological phenomena. Through this perspective of analysis, we contribute with a configuration that incorporates diagnostic components, its implementation and the assessment of risk scenarios. The results in each of the different stages reveal that the modeling, simulation, analysis and treatment of the data, are a vital factor in explaining the effects, as well as their ability to articulate high-value solutions for organizationsLa gestión del riesgo (risk management) es un enfoque estructurado que incorpora la incertidumbre relativa a una amenaza, vinculada a una secuencia de actividades inherentemente humanas que incluyen la evaluación del riesgo, así como otras estrategias para su mitigación. El objetivo, es reducir diferentes riesgos relativos a un ámbito preseleccionado. Su clasificación es diversa, por ejemplo: las amenazas por factores asociados al medio ambiente, la tecnología, los errores humanos, las organizaciones, entre otros. La valoración del riesgo, se está consolidando como una herramienta de soporte para el análisis de decisiones en condiciones de incertidumbre, particularmente para los sistemas complejos, como las cadenas de suministro. Sin duda, la gestión del riesgo cobra relevancia siendo un componente crítico en las decisiones de gestión, al ser un proceso continuo. Desde esta perspectiva, a través de los enfoques paramétricos y del análisis multivariante, ha sido posible estudiar y representar los datos que resultan de observar más de una variable estadística sobre una población en particular. Para lo cual se ha diseñado y validado un instrumento para el acopio de información a través de la configuración de una interfaz online. Hemos orientado nuestros esfuerzos para conocer cual es la percepción del riesgo, las estrategias de colaboración, así como la identificación de las prácticas logísticas, dado un conglomerado de actores, particularmente ante contextos de riesgo asociados a los fenómenos hidrometereológicos. En una segunda instancia, basado en los pasos anteriores, hemos propuesto la modelación y el enfoque de simulación de Montecarlo para identificar el impacto de los riesgos competitivos. Este paradigma, se ha consolidado en la ciencia médica, pero hoy día se pueden encontrar aportaciones en las ciencias sociales, la ingeniería, actuaría, entre otros. Nuestro enfoque, propone una selección de causas de fallo perteneciente a un conjunto de eventos posibles, los cuales fueron identificados en la fase de diagnóstico. La modelación la especificamos a través de la identificación y discriminación de riesgos para cada nivel de suministro. A través de la simulación de riesgos competitivos, fue estimada la incidencia acumulada, las probabilidades de ocurrencia y las tasas de cumplimiento para un modelo multinivel de suministro. También, se formuló una solución alterna y versátil para diversificar los instrumentos, métodos y técnicas de tratamiento del riesgo en cadenas de suministro. La solución, estima la probabilidad de fallo para una causa dada, antes del tiempo de vencimiento específico. Finalmente, se propuso un estudio de caso en donde y mediante el enfoque de simulación se valoró el comportamiento de un conjunto de instancias, cuyo componente de análisis está supeditado especialmente a las disrupciones súbitas de suministros, asociadas a los fenómenos hidrometereológicos. Mediante esta perspectiva de análisis, contribuimos con una configuración que incorpora componeantes de diagnóstico, su implementación y la valoración de escenarios de riesgo. Los resultados en cada una de las diferentes etapas, revelan que la modelación, la simulación, el análisis y el tratamiento de los datos, son un factor vital para explicar los efectos, así como su capacidad para articular soluciones de alto valor para las organizaciones.Postprint (published version

Energy Management and Environmental Sustainability of the Canadian Oil Sands Industry

By 2030 the worldwide energy demand is expected to increase by twofold, in which fossil fuels inevitably will still play a major role in this transition. Canadian oil sands, the second largest proven oil reserves, represent a major pillar in providing energy and economic security in North America. Their development on a large scale is hindered due to associated environmental impacts, which include greenhouse gas emissions, water usage, and management of by-products of downstream operations (e.g. Sulfur, petroleum coke, etc.). In this work optimization techniques are employed to address the management of various environmental issues while minimizing the cost of operations of the oil sands industry. In this context, this thesis makes four principal contributions. First, an extensive review is conducted on potential production pathways of renewable energy that can be integrated in the energy infrastructure of oil sands. Renewable technologies such as wind, geothermal, hydro, bioenergy, and solar are considered the most environmentally benign options for energy production that would contribute in achieving significant carbon emissions reductions. A mixed integer non-linear optimization model is developed to simultaneously optimize the capacity expansion and new investment decisions of both conventional and renewable energy technologies, and determine the optimal configurations of oil producers. The rolling horizon approach is used for the consecutive planning of multiple operational periods. To illustrate the applicability of the model, it was applied to a case study based on operational data for oil sands operators in Alberta for the period of 2010 – 2025. Second, a generalized optimization model was developed for the energy planning of energy intensive industries. An extensive superstructure was developed that incorporates conventional, renewable, nuclear, and gasification of alternative fuels (e.g. petroleum coke, asphaltenes, etc.) technologies for the production of energy in the form of power, heat and hydrogen. Various carbon mitigation measures were incorporated, including carbon capture and sequestration, and purchase of carbon credits to satisfy emission targets. Finally, the superstructure incorporated the possibility of selling excess energy commodities in competitive markets. The superstructure is represented by a multi-period mixed integer optimization model with the objective of identifying the optimal set of energy supply technologies to satisfy a set of demands and emission targets at the minimum cost. Time-dependent parameters are incorporated in the model formulation, including energy demands, fuel prices, emission targets, carbon tax, construction lead time, etc. The model is applied to a case study based on the oil sands operations over the planning period 2015–2050. A scenario based approach is used to investigate the effect of variability in energy demand levels, various carbon mitigation policies, and variability in fuel and energy commodity prices. Third, a multi-objective and multi-period mixed integer linear programming model is developed for the integrated planning and scheduling of the energy infrastructure of the oil sands industry incorporating intermittent renewable energy. The contributions of various energy sources including conventional, renewable, and nuclear are investigated using a scenario based approach. Power-to-gas for energy storage is incorporated to manage surplus power generated from intermittent renewable energy sources, particularly wind. The wind-electrolysis system incorporates two hydrogen recovery pathways, which are power-to-gas and power-to-gas-to-power using natural gas generators. The model takes into account interactions with the local Alberta grid by incorporating unit commitment constraints for the grid’s existing power generation units. Three objective functions are considered, which are the total system cost, grid operating cost and total emissions. The epsilon constraint method is used to solve the multi-objective aspect of the proposed model. Fourth, extensive research has been done on the components that constitute the sulfur supply chain, including sulfur recovery, storage, forming, and distribution. These components are integrated within a single framework to assist in the design optimization of sulfur supply chains. This represents a starting point in understanding the trade-offs involved in the sulfur supply chain from an optimization point of view. Optimization and mathematical modeling techniques were implemented to generate a decision support system that will provide an indication of the optimal design and configuration of sulfur supply chains. The resulting single-period mixed-integer linear programming model was aimed at minimizing total capital and operating costs. The model was illustrated through a case study based on Alberta’s Industrial Heartland. A deterministic approach in an uncertain environment was implemented to investigate the effect of supply and demand variability on the design of the supply chain. This was applied to two scenarios, which are steady state operation and sulfur surplus accumulation. The model identified the locations of forming facilities, the forming, storage and transportation technologies, and their capacities. The contributions of this thesis are intended to support effective carbon mitigation policy making and to address the environmental sustainability of the oil sands industry