Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores
Tablas, figuras
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2025
- Institución:
- Universidad de Caldas
- Repositorio:
- Repositorio Institucional U. Caldas
- Idioma:
- spa
eng
- OAI Identifier:
- oai:repositorio.ucaldas.edu.co:ucaldas/22653
- Acceso en línea:
- https://repositorio.ucaldas.edu.co/handle/ucaldas/22653
- Palabra clave:
- 620 - Ingeniería y operaciones afines
2. Ingeniería y Tecnología
Transporte Marítimo
Maritime Transport
Comercio Exterior
Optimización
Logística
Medio Ambiente
Foreign Trade
Optimization
Logistics
Environmental
Ingeniería
Transporte marítimo
Tecnología de materiales
- Rights
- License
- https://creativecommons.org/licenses/by-nc-nd/4.0/
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REPOUCALDA |
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Repositorio Institucional U. Caldas |
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| dc.title.none.fl_str_mv |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores Multi-objective optimization of logistics and environmental processes in maritime container transportation |
| title |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| spellingShingle |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores 620 - Ingeniería y operaciones afines 2. Ingeniería y Tecnología Transporte Marítimo Maritime Transport Comercio Exterior Optimización Logística Medio Ambiente Foreign Trade Optimization Logistics Environmental Ingeniería Transporte marítimo Tecnología de materiales |
| title_short |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| title_full |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| title_fullStr |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| title_full_unstemmed |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| title_sort |
Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedores |
| dc.contributor.none.fl_str_mv |
Isaza, Gustavo Toro-Ocampo, Eliana Mirledy Jaramillo-Garzón, Jorge Alberto Inteligencia Artificial Franco Baquero, John Fredy Villegas Ramírez, Juan Guillermo Gutiérrez Mosquera, Luis Fernando |
| dc.subject.none.fl_str_mv |
620 - Ingeniería y operaciones afines 2. Ingeniería y Tecnología Transporte Marítimo Maritime Transport Comercio Exterior Optimización Logística Medio Ambiente Foreign Trade Optimization Logistics Environmental Ingeniería Transporte marítimo Tecnología de materiales |
| topic |
620 - Ingeniería y operaciones afines 2. Ingeniería y Tecnología Transporte Marítimo Maritime Transport Comercio Exterior Optimización Logística Medio Ambiente Foreign Trade Optimization Logistics Environmental Ingeniería Transporte marítimo Tecnología de materiales |
| description |
Tablas, figuras |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025-09-04T21:24:06Z 2025-09-04T21:24:06Z 2025 2035-09-04 |
| dc.type.none.fl_str_mv |
Trabajo de grado - Doctorado http://purl.org/coar/resource_type/c_db06 Text info:eu-repo/semantics/doctoralThesis |
| dc.identifier.none.fl_str_mv |
https://repositorio.ucaldas.edu.co/handle/ucaldas/22653 Universidad de Caldas Repositorio Institucional Universidad de Caldas repositorio.ucaldas.edu.co |
| url |
https://repositorio.ucaldas.edu.co/handle/ucaldas/22653 |
| identifier_str_mv |
Universidad de Caldas Repositorio Institucional Universidad de Caldas repositorio.ucaldas.edu.co |
| dc.language.none.fl_str_mv |
spa eng |
| language |
spa eng |
| dc.relation.none.fl_str_mv |
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Universidad de Caldas Facultad de Inteligencia Artificial e Ingenierías Colombia, Caldas, Manizales Doctorado en Ingeniería |
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Universidad de Caldas Facultad de Inteligencia Artificial e Ingenierías Colombia, Caldas, Manizales Doctorado en Ingeniería |
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Optimización multiobjetivo de procesos logístico-ambientales aplicados al transporte marítimo de contenedoresMulti-objective optimization of logistics and environmental processes in maritime container transportation620 - Ingeniería y operaciones afines2. Ingeniería y TecnologíaTransporte MarítimoMaritime TransportComercio ExteriorOptimizaciónLogísticaMedio AmbienteForeign TradeOptimizationLogisticsEnvironmentalIngenieríaTransporte marítimoTecnología de materialesTablas, figurasEl transporte marítimo de contenedores constituye una columna vertebral del comercio internacional, pero enfrenta crecientes presiones para reducir sus costos logísticos y su impacto ambiental. En este contexto, la presente tesis doctoral aborda de forma integral el diseño e implementación de un modelo matemático y computacional orientado a la optimización logística bajo principios de sostenibilidad ambiental, dentro del marco de la logística verde. El trabajo se fundamenta en una perspectiva multiobjetivo que considera simultáneamente la eficiencia operativa y la reducción de emisiones, integrando variables logísticas y ambientales en un solo sistema de decisión. Para lograr este propósito, se desarrolló una metodología estructurada en tres fases, alineadas con los objetivos específicos: la identificación y validación de datos relevantes, el modelado matemático y la construcción de una solución aproximada basada en inteligencia artificial. La primera fase permitió clasificar y validar las variables logísticas y ambientales críticas para el transporte marítimo de contenedores, generando un conjunto de datos aplicables a escenarios reales. En la segunda fase, se formularon dos enfoques multiobjetivo complementarios. El primero consistió en un modelo de programación lineal entera mixta (MILP), en el que los costos logísticos y ambientales fueron ponderados mediante los parámetros α y β, otorgando la posibilidad de ajustar las prioridades entre eficiencia económica y sostenibilidad ambiental, condición que relaja la complejidad del problema y constituye uno de los aportes clave de la investigación, al ofrecer una herramienta adaptable a diferentes contextos estratégicos y operativos. El segundo correspondió a una formulación explícita bajo el enfoque ε-constraint, en la que se optimizó uno de los objetivos mientras se imponían límites al otro, permitiendo explorar el frente de Pareto y comprender el comportamiento del sistema bajo diferentes niveles de restricción ambiental. Para resolver la complejidad del problema, se diseñó una técnica bioinspirada denominada Foam 2- Echelon Ship Routing Problem (F2-ESRP), que simula el comportamiento dinámico de la espuma al buscar las conexiones más cercanas y eficientes dentro de una red de 90 puertos marítimos. Esta metodología se estructuró en tres etapas: agrupamiento geográfico de puertos (clustering), ruteo intra-clúster y ruteo inter-clúster mediante el algoritmo de Christofides, permitiendo una asignación optimizada de flotas que van desde embarcaciones tipo feeder hasta buques Panamax y Post-Panamax. El modelo también incorporó estimaciones de costos y emisiones utilizando modelos de regresión exponencial y potencial, considerando variables como tarifas de flete, factores de ajuste por combustible (BAF) y emisiones de CO2, SO2, NOx y PM10, capturando las relaciones no lineales entre distancia, costo y huella ambiental. Los resultados obtenidos demostraron que la configuración óptima (α = 0.8, β = 0.2) permitió alcanzar un equilibrio eficiente entre sostenibilidad y rendimiento logístico, logrando reducciones significativas tanto en los costos totales como en las emisiones. Además, se evidenció una mejora notable en la eficiencia computacional, con tiempos de ejecución que disminuyeron de 2 minutos a 16 segundos en rutas específicas, y con resolución de componentes tipo TSP en apenas 2 segundos. Estos hallazgos confirman la viabilidad práctica del modelo y su potencial como herramienta robusta, escalable y adaptable para la planificación logística en operaciones marítimas a gran escala. La tesis ha sido ampliamente divulgada mediante múltiples publicaciones científicas que abordan desde revisiones de puertos inteligentes hasta análisis de estrategias sostenibles en transporte marítimo, consolidando así una contribución científica y metodológica relevante para el avance de la logística verde y la gestión sostenible de cadenas de suministro globales.Containerized maritime transport serves as a fundamental backbone of international trade but faces increasing pressure to reduce both logistical costs and environmental impacts. In this context, this doctoral thesis presents a comprehensive approach to the design and implementation of a mathematical and computational model aimed at logistics optimization grounded in environmental sustainability principles, within the framework of green logistics. The work is based on a multi-objective perspective that simultaneously considers operational efficiency and emission reduction, integrating logistical and environmental variables into a unified decision- making system. To achieve this objective, a methodology structured in three phases was developed, aligned with the specific research goals: data identification and validation, mathematical modeling, and the construction of an approximate solution leveraging artificial intelligence techniques. The first phase enabled the classification and validation of critical logistical and environmental variables relevant to container maritime transport, producing a dataset applicable to real-world scenarios. In the second phase, two complementary multi- objective modeling approaches were formulated. The first approach involved a Mixed-Integer Linear Programming (MILP) model where logistical and environmental costs were weighted using parameters α and β, allowing for flexible prioritization between economic efficiency and environmental sustainability. This relaxation of problem complexity constitutes a key contribution of the research by providing an adaptable tool suitable for diverse strategic and operational contexts. The second approach employed an explicit ε-constraint formulation, optimizing one objective while imposing limits on the other, facilitating exploration of the Pareto front and enhancing understanding of system behavior under varying environmental restrictions. To address the problem’s inherent complexity, a bioinspired technique termed the Foam 2- Echelon Ship Routing Problem (F2-ESRP) was developed. This method simulates the dynamic behavior of foam as it seeks the shortest and most efficient connections within a network of 90 maritime ports. The methodology comprises three stages: geographic clustering of ports, intra- cluster routing, and inter-cluster routing via the Christofides algorithm, enabling optimized fleet allocation spanning feeder vessels to Panamax and Post-Panamax ships. The model also incorporated cost and emission estimates using exponential and power regression models, considering variables such as freight rates, Bunker Adjustment Factors (BAF), and emissions of CO2, SO2, NOx, and PM10, thereby capturing nonlinear relationships among distance, cost, and environmental footprint. Results demonstrated that the optimal configuration (α = 0.8, β = 0.2) achieved an effective balance between sustainability and logistical performance, yielding significant reductions in both total costs and emissions. Moreover, computational efficiency improved markedly, with execution times for specific routes reduced from 2 minutes to 16 seconds, and Traveling Salesman Problem (TSP)-type components solved in just 2 seconds. These findings validate the practical viability of the model and underscore its potential as a robust, scalable, and adaptable tool for logistics planning in large-scale maritime operations. The thesis has been widely disseminated through multiple scientific publications, covering topics ranging from smart port reviews to sustainable maritime transport strategies, thus consolidating a significant scientific and methodological contribution toward advancing green logistics and sustainable management of global supply chains.Introducción -- Planteamiento del problema -- Justificación -- Marco teórico y antecedentes -- Generalidades del transporte marítimo -- Análisis de las investigaciones en logística del transporte marítimo -- Generalidades logísticas del transporte marítimo -- Logística verde en el transporte marítimo de contenedores -- Técnicas de inteligencia artificial en la logística del transporte -- Objetivos -- Metodología -- Identificación y validación de variables ambientales y logísticas -- Integración de variables en un modelo matemático -- Metodología de optimización logística -- Estructura del documento -- Resultados de investigación -- Operational efficiency and sustainability in smart ports: A comprehensive review -- Advances and emerging research trends in maritime transport logistics: environment, port competitiveness and foreign trade -- Mathematical models for the optimization of maritime routes in container transportation -- Trends and strategies in sustainable maritime transport: Insights from global research -- Scientific mapping and research perspectives of the vehicle routing problem: An approach from sustainability strategies -- Cost and variable analysis in international maritime transport: Strategies for logistic optimization -- Optimisation of maritime routes: An intelligent approach to logistics efficiency -- Foam 2-Echelon Ship Routing Problem: A bioinspired methodology for route optimization and ship allocation in maritime transport -- Conclusiones generales -- Referencias -- Annex 1. Actual and estimated costs for parameter calibration -- Annex 2. Results of the sensitivity analysis by instancesDoctoradoPara el desarrollo de la presente tesis doctoral y el logro de los objetivos se consideró una secuencia de actividades agrupadas de forma lógica como se detalla en la Figura 3. El esquema metodológico se encuentra dividido en tres secciones, cada una relacionada con los objetivos específicos de la siguiente manera: identificación y validación de variables ambientales y logísticas, integración de variables en un modelo matemático, y construcción y validación de una metodología de solución aproximada para la optimización logística de actividades de transporte marítimo de contenedores. La primera sección, variables ambientales y logísticas, considera tres etapas para la definición, identificación y validación de las variables de estudio. En su desarrollo se realizó la identificación y análisis de las variables ambientales y logísticas que intervienen en los procesos asociados al transporte marítimo; además de la construcción de un conjunto de datos, los cuales corresponden al insumo para las siguientes actividades. La determinación de las variables y su clasificación fueron operaciones críticas para la optimización de los procesos considerados en las etapas posteriores. La siguiente sección, denominada modelamiento matemático, englobó las actividades relacionadas con la construcción y validación de un modelo matemático para la optimización de las variables identificadas en la primera parte. Dos etapas se desarrollaron para su cumplimiento, la construcción y la aplicación, donde se definieron las particularidades de las variables a introducir en el modelo matemático, y la posterior implementación y validación en un conjunto de datos obtenidos en un caso de aplicación real. La sección final integró el análisis de las técnicas de inteligencia artificial para resolver problemas de optimización de actividades logísticas asociadas al transporte marítimo. Durante esta fase se realizaron tres procesos, evaluación, construcción y validación de metodologías de solución. La evaluación permitió identificar las técnicas a implementar de acuerdo a los parámetros, variables y criterios de inclusión. Seguidamente, se diseñó una metodología de solución aproximada para los procesos asociados a la logística verde previamente identificados. Finalmente, se desarrolló una etapa de validación para evaluar la eficiencia de la metodología desarrollada.Doctor(a) en IngenieríaUniversidad de CaldasFacultad de Inteligencia Artificial e IngenieríasColombia, Caldas, ManizalesDoctorado en IngenieríaIsaza, GustavoToro-Ocampo, Eliana MirledyJaramillo-Garzón, Jorge AlbertoInteligencia ArtificialFranco Baquero, John FredyVillegas Ramírez, Juan GuillermoGutiérrez Mosquera, Luis FernandoALZATE, PAOLA2025-09-04T21:24:06Z2035-09-042025-09-04T21:24:06Z2025Trabajo de grado - Doctoradohttp://purl.org/coar/resource_type/c_db06Textinfo:eu-repo/semantics/doctoralThesis308 páginasapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttps://repositorio.ucaldas.edu.co/handle/ucaldas/22653Universidad de CaldasRepositorio Institucional Universidad de Caldasrepositorio.ucaldas.edu.cospaengAbbasi-Pooya A., Husseinzadeh Kashan A. (2017). 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