Optimising and recognising 2-stage delivery chains with time windows

In logistic delivery chains time windows are common. An arrival has to be in a certain time interval, at the expense of waiting time or penalties if the time limits are exceeded. This paper looks at the optimal placement of those time intervals in a specific case of a barge visiting two ports in sequence. For the second port a possible delay or penalty should be incorporated. Next, recognising these penalty structures in data is analysed to if see certain patterns in public travel data indicate that a certain dependency exists

Workload Equity in Vehicle Routing Problems: A Survey and Analysis

Over the past two decades, equity aspects have been considered in a growing number of models and methods for vehicle routing problems (VRPs). Equity concerns most often relate to fairly allocating workloads and to balancing the utilization of resources, and many practical applications have been reported in the literature. However, there has been only limited discussion about how workload equity should be modeled in VRPs, and various measures for optimizing such objectives have been proposed and implemented without a critical evaluation of their respective merits and consequences. This article addresses this gap with an analysis of classical and alternative equity functions for biobjective VRP models. In our survey, we review and categorize the existing literature on equitable VRPs. In the analysis, we identify a set of axiomatic properties that an ideal equity measure should satisfy, collect six common measures, and point out important connections between their properties and those of the resulting Pareto-optimal solutions. To gauge the extent of these implications, we also conduct a numerical study on small biobjective VRP instances solvable to optimality. Our study reveals two undesirable consequences when optimizing equity with nonmonotonic functions: Pareto-optimal solutions can consist of non-TSP-optimal tours, and even if all tours are TSP optimal, Pareto-optimal solutions can be workload inconsistent, i.e. composed of tours whose workloads are all equal to or longer than those of other Pareto-optimal solutions. We show that the extent of these phenomena should not be underestimated. The results of our biobjective analysis are valid also for weighted sum, constraint-based, or single-objective models. Based on this analysis, we conclude that monotonic equity functions are more appropriate for certain types of VRP models, and suggest promising avenues for further research.Comment: Accepted Manuscrip

A Hybrid Heuristic for a Broad Class of Vehicle Routing Problems with Heterogeneous Fleet

We consider a family of Rich Vehicle Routing Problems (RVRP) which have the particularity to combine a heterogeneous fleet with other attributes, such as backhauls, multiple depots, split deliveries, site dependency, open routes, duration limits, and time windows. To efficiently solve these problems, we propose a hybrid metaheuristic which combines an iterated local search with variable neighborhood descent, for solution improvement, and a set partitioning formulation, to exploit the memory of the past search. Moreover, we investigate a class of combined neighborhoods which jointly modify the sequences of visits and perform either heuristic or optimal reassignments of vehicles to routes. To the best of our knowledge, this is the first unified approach for a large class of heterogeneous fleet RVRPs, capable of solving more than 12 problem variants. The efficiency of the algorithm is evaluated on 643 well-known benchmark instances, and 71.70\% of the best known solutions are either retrieved or improved. Moreover, the proposed metaheuristic, which can be considered as a matheuristic, produces high quality solutions with low standard deviation in comparison with previous methods. Finally, we observe that the use of combined neighborhoods does not lead to significant quality gains. Contrary to intuition, the computational effort seems better spent on more intensive route optimization rather than on more intelligent and frequent fleet re-assignments

GVNS for a real-world rich vehicle routing problem with time windows

Rich Vehicle Routing Problems are vehicle routing problems (VRPs) that deal with additional constraints, which aim to better take into account the particularities of real-world applications. They combine multiple attributes, which constitute a complement to the traditional models. This work proposes an adaptive solution method based on metaheuristics for solving a Rich Vehicle Routing Problem with Time Windows. This software has been embedded into the fleet management system of a company in the Canary Islands. The attributes considered by the company are a fixed heterogeneous fleet of vehicles, soft and multiple time windows, customer priorities and vehicle–customer constraints. Furthermore, the company requires the consideration of several objective functions that include travelled distance and time/distance balance. Exact algorithms are not applicable when solving real-life large VRP instances. This work presents a General Variable Neighbourhood Search metaheuristic, which obtains high quality solutions. The computational experiments are presented in four sections, which comprise the parameter setting, the analysis of the effect of the considered attributes, the comparative with the literature for the standard VRP with Time Windows, and the study of the solutions provided by the algorithm when compared with the solutions implemented by the company.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (project TIN2012-32608) and the Spanish Ministry of Industry, Tourism and Trade (project TSI-020100-2011-298)

Gestaltung nachhaltiger Logistik-Konzepte im urbanen Wirtschaftsverkehr : Entscheidungsunterstützung mit Optimierungsmodellen

Die vorliegende kumulative Dissertation stellt die Zusammenfassung von zehn wissenschaftlichen Artikeln im Bereich des urbanen Wirtschaftsverkehrs dar. Dabei geht es grundsätzlich um die Untersuchung neuer Logistik-Konzepte als Lösungsansatz für eine gleichzeitige Berücksichtigung ökonomischer und ökologischer Ziele bei der Ausübung von Transportaktivitäten in urbanen Räumen. Dazu werden mathematische Optimierungsmodelle und Entscheidungsunterstützungssysteme präsentiert, welche den Zielkonflikt zwischen einer Kosten- und einer Emissionsminimierung adressieren. Diese sind durch die Anwendung von Methoden des Operations Research und der Informationssystem-Forschung entstanden. Darüber hinaus erfolgt die kritische Reflektion über die behandelten Themen, die genutzten Forschungsmethoden und die entwickelten Lösungsansätze. Drei Themen werden in der Dissertation ausführlich dargestellt: (1) Nachhaltige urbane Paketzustellung: Es wird ein Optimierungsmodell präsentiert, welches in ein Entscheidungsunterstützungssystem eingebettet ist und die bestmögliche Gestaltung eines alternativen Logistik-Konzepts für die Zustellung von Paketen in Städten ermöglicht. Dabei geht es um die Bestimmung der Positionen von Mikro-Depots als Orte der Zwischenlagerung sowie der dazugehörigen Fahrzeugflotte. (2) Nachhaltige e-Grocery Zustellung: Für die Lieferung von online bestellten Verbrauchsgütern wie Lebensmitteln oder Haushaltsartikeln wird ein neues Logistik-Konzept entworfen. Hierbei erfolgt eine Verkürzung der letzten Meile durch den Einsatz von temperierten Umschlagspunkten sowie eine Integration von Lastenfahrrädern und Kunden-Selbstabholungen. Ein dreistufiger Lösungsansatz ermöglicht die Optimierung der Standorte der Umschlagspunkten sowie der Fahrzeugrouten. (3) Individuelle Routenoptimierung: Es wird ein Entscheidungsunterstützungssystem zur Modellierung sowie Lösung von individualisierbaren Tourenplanungsproblemen präsentiert. Das flexible Tool ermöglicht die Abbildung von benutzerspezifischen Problemcharakteristika und die Umwandlung in ein entsprechendes Optimierungsmodell, sodass diverse Branchen bei der Routenplanung unterstützt werden können

Algorithms for vehicle routing problems with heterogeneous fleet, flexible time windows and stochastic travel times

Orientador: Vinícius Amaral ArmentanoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Este trabalho aborda três variantes multiatributo do problema de roteamento de veículos. A primeira apresenta frota heterogênea, janelas de tempo invioláveis e tempos de viagem determinísticos. Para resolvê-la, são propostos algoritmos ótimos baseados na decomposição de Benders. Estes algoritmos exploram a estrutura do problema em uma formulação de programação inteira mista, e três diferentes técnicas são desenvolvidas para acelerá-los. A segunda variante contempla os atributos de frota heterogênea, janelas de tempo flexíveis e tempos de viagem determinísticos. As janelas de tempo flexíveis permitem o início do serviço nos clientes com antecipação ou atraso limitados em relação às janelas de tempo invioláveis, com custos de penalidade. Este problema é resolvido por extensões dos algoritmos de Benders, que incluem novos algoritmos de programação dinâmica para a resolução de subproblemas com a estrutura do problema do caixeiro viajante com janelas de tempo flexíveis. A terceira variante apresenta frota heterogênea, janelas de tempo flexíveis e tempos de viagem estocásticos, sendo representada por uma formulação de programação estocástica inteira mista de dois estágios com recurso. Os tempos de viagem estocásticos são aproximados por um conjunto finito de cenários, gerados por um algoritmo que os descreve por meio da distribuição de probabilidade Burr tipo XII, e uma matheurística de busca local granular é sugerida para a resolução do problema. Extensivos testes computacionais são realizados em instâncias da literatura, e as vantagens das janelas de tempo flexíveis e dos tempos de viagem estocásticos são enfatizadasAbstract: This work addresses three multi-attribute variants of the vehicle routing problem. The first one presents a heterogeneous fleet, hard time windows and deterministic travel times. To solve this problem, optimal algorithms based on the Benders decomposition are proposed. Such algorithms exploit the structure of the problem in a mixed-integer programming formulation, and three algorithmic enhancements are developed to accelerate them. The second variant comprises a heterogeneous fleet, flexible time windows and deterministic travel times. The flexible time windows allow limited early and late servicing at customers with respect to their hard time windows, at the expense of penalty costs. This problem is solved by extensions of the Benders algorithms, which include novel dynamic programming algorithms for the subproblems with the special structure of the traveling salesman problem with flexible time windows. The third variant presents a heterogeneous fleet, flexible time windows and stochastic travel times, and is represented by a two-stage stochastic mixed-integer programming formulation with recourse. The stochastic travel times are approximated by a finite set of scenarios generated by an algorithm which describes them using the Burr type XII distribution, and a granular local search matheuristic is suggested to solve the problem. Extensive computational tests are performed on instances from the literature, and the advantages of flexible windows and stochastic travel times are stressed.DoutoradoAutomaçãoDoutor em Engenharia Elétrica141064/2015-3CNP

Diseño y aplicación de una herramienta para la optimización de rutas de vehículos con aspectos medioambientales

En la actualidad, en torno al 90% de la población de la Unión Europea se encuentra expuesta a altas concentraciones de algunos de los contaminantes atmosféricos más nocivos para la salud, reduciendo la esperanza de vida de la población y ocasionando un fuerte impacto económico en el producto interior bruto de los países. Dentro de los sectores económicos, el transporte se presenta como una de las principales fuentes de contaminación ya que genera niveles nocivos de emisiones contaminantes y es el responsable de hasta el 24% de las emisiones de gases de efecto invernadero (GEI) en la Unión Europea. Estas emisiones dependen en gran medida de los combustibles utilizados, de la carga y tecnología del motor de los vehículos y principalmente de las distancias recorridas. El problema de la distribución de productos desde los almacenes a los usuarios finales juega un papel central en la gestión de algunos sistemas logísticos, donde la determinación de rutas de reparto eficientes es fundamental en la reducción de costes. Este problema en la vida real, se caracteriza por disponer las empresas de distribución de una flota heterogénea, en la que vehículos con diferentes características son incorporados a lo largo del tiempo para una mejor adaptación a las demandas de los clientes. Entre las características más destacadas se encuentran vehículos con diferentes capacidades y antigüedad, usos de combustibles alternativos y tecnología del motor. Por todo ello, en el contexto actual la componente medioambiental tiene que ser añadida en el proceso de toma de decisiones a las estrategias logísticas tradicionales, basadas en costes y tiempos. Esta Tesis Doctoral se ha centrado en su mayor parte al desarrollo de nuevos modelos y algoritmos para la resolución del Problema de Enrutamiento de Vehículos con Flota Fija Heterogénea y Ventanas de Tiempo (HVRPTW), con la consideración adicional de reducir las emisiones de GEI y de partículas contaminantes. La formulación del problema se realiza desde dos perspectivas muy diferenciadas. La primera de ellas incorpora una metodología basada en la estimación de los costes asociados a las externalidades presentes en las actividades del transporte. La segunda perspectiva comprende técnicas de optimización multiobjetivo con asignación de preferencias a priori, en el que el decisor puede establecer sus preferencias por adelantado. La elaboración de las rutas eco-eficientes se plantea mediante modelos lineales de programación matemática y se resuelve usando técnicas cuantitativas. Estas técnicas comprenden algoritmos heurísticos y metaheurísticos que combinan diversos procedimientos avanzados para tratar la complejidad del problema. En particular, esta Tesis describe una heurística de inserción secuencial semi-paralela y una metaheurística híbrida de búsqueda de entorno variable descendente con búsqueda tabú y lista de espera, que introduce una mayor flexibilidad para la resolución de cualquier variante del problema HVRPTW. Los algoritmos han sido aplicados a problemas típicos de recogida y reparto de mercancías de la literatura científica y a un caso real, que comprende la planificación de rutas y personal en una empresa de servicios con características y restricciones muy peculiares. Los resultados demuestran que el algoritmo resuelve de manera eficiente la variante del problema abordado y es extensible para la resolución de otras variantes. El resultado de la Tesis es el desarrollo de una herramienta para la ayuda a la toma de decisiones en el diseño y control de rutas eco-eficientes. Dicha herramienta podrá integrarse con el sistema de información geográfica (GIS) particular de cada empresa y permitirá la visualización de las rutas eco-eficientes, evaluando el impacto producido en los ámbitos económico, energético, operativo y medioambiental. Por ello, la herramienta tendrá un impacto económico directo sobre los usuarios finales y permitirá la comparación de rutas y resultados obtenidos a partir de diferentes alternativas, logrando una mayor competitividad y el cumplimiento de los compromisos de sostenibilidad en la empresa. Por otro lado, a nivel global, la herramienta contribuye a una mejora social derivada de una reducción del consumo energético y de una disminución de las emisiones contaminantes de las flotas de transporte de mercancías por carretera, que tienen un impacto a nivel local, nacional e internacional. En este sentido, la Tesis Doctoral contribuye claramente al desarrollo estratégico del sector transporte de mercancías, aumentando la eficiencia de las flotas de transporte por carretera y logrando una mayor sostenibilidad y competitividad.Nowadays, around 90% of city dwellers in the European Union are exposed to high concentrations of healthharmful pollutants, reducing the life expectancy of the population and having a large impact on the gross domestic product of European countries. Among the economic sectors, transport is presented as one of the main sources of pollution because it generates harmful levels of emissions and is responsible for up to 24% of greenhouse gases (GHG) emissions in the European Union. These emissions depend heavily on the fuel type used, the carried load, the engine technology and the total distance covered. The problem of the distribution of goods from warehouses to end users plays a central role in the logistics systems management, where the design of efficient routes is critical in reducing costs. This real-life problem is characterized by presenting a heterogeneous fleet where vehicles with different features are incorporated over the time for a better adaptation to the changing customer demands. These features include vehicles with different capacities and age, alternative fuels and motor technologies. Therefore, in the present context, environmental targets are to be added to traditional logistics strategies based on cost and time in the decision making process. The research of this Thesis has focused on the development of new mathematical models and algorithms for solving the Fixed Fleet Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) with the additional consideration of reducing GHG and pollutants emissions. The formulation of the problem is made from two different perspectives. The first incorporates a methodology based on the estimation of the external costs of transport activities. The second perspective comprises a multiobjective optimization method with a priori articulation of preferences, in which the decision maker can establish the preferences in advance. The design of eco-efficient routes is proposed by linear mathematical programming models and is solved using quantitative techniques. These techniques include heuristics and metaheuristics that combine various advanced procedures to deal with the complexity of the problem. In particular, this Thesis describes a semi-parallel insertion heuristic and a hybrid variable neighborhood descent metaheuristic based on a tabu search algorithm for the local search and a holding list that achieves flexibility for solving any HVRPTW variant. The algorithms have been applied to benchmark problems from the scientific literature and to a real-world case that deals with a routing and scheduling problem in a service company with particular characteristics and constraints. The results show that the algorithm efficiently solves the problem addressed and it can be extended to other problem variants. The result of the Thesis is the development of a decision making process tool aimed to help in the design and control of eco-efficient routes. This tool can be integrated with the particular geographic information system (GIS) of each company, allowing the display of eco-efficient routes and assessing the economic, energy, operational and environmental impacts. Therefore, the tool will have an economic impact on the end users, with a comparison of the final routes and the results obtained from different alternatives, achieving greater competitiveness and fulfilling the sustainability commitments in the company. On the other hand, the tool globally contributes to a social improvement resulting from the fuel consumption and pollutant emissions reductions from road transport, which have an impact at local, national and international level. In this sense, the Thesis clearly contributes to the strategic development of the transport sector, increasing the efficiency of road transport fleets and achieving greater sustainability and competitiveness