Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks

A main challenge in transporting cargo for United States Transportation Command (USTRANSCOM) is in mode selection or integration. Demand for cargo is time sensitive and must be fulfilled by an established due date. Since these due dates are often inflexible, commercial carriers are used at an enormous expense, in order to fill the gap in organic transportation asset capacity. This dissertation develops a new methodology for transportation capacity assignment to routes based on the Resource Constrained Shortest Path Problem (RCSP). Routes can be single or multimodal depending on the characteristics of the network, delivery timeline, modal capacities, and costs. The difficulty of the RCSP requires use of metaheuristics to produce solutions. An Ant Colony System to solve the RCSP is developed in this dissertation. Finally, a method for generating near Pareto optimal solutions with respect to the objectives of cost and time is developed

Airport airside balanced capacity usage and planning

U doktorskoj disertaciji je predložen postupak za analizu kapaciteta vazdušne strane aerodroma, za zadata fizička i operativna ograničenja, i zadate karakteristike potražnje. Ovaj postupak podrazumeva povezivanje (postojećeg) modela za procenu kapaciteta sistema poletno-sletnih staza sa (proširenim) modelom za procenu kapaciteta pristanišne platforme, kroz njihovu funkcionalnu vezu. Cilj ove doktorske disertacije je bio vrednovanje i, po potrebi, modifikovanje i proširenje postojećih modela za procenu kapaciteta platforme, kao i definisanje funkcionalne veze između poletno-sletne staze i platforme za različite tipove saobraćaja. Postojeći modeli su prošireni tako da uzimaju u obzir ograničenja po tipu aviona i korisnicima (npr. aviokompanije), kao i po vrsti saobraćaja. U cilju analize osetljivosti, predlažene su obvojnice za prikazivanje kapaciteta platforme određene konfiguracije, u zavisnosti od strukture potražnje u odnosu na glavne uticajne faktore. Analiza je obuhvatila dva osnovna tipa aerodroma sa aspekta njihove uloge u mrežama vazdušnog saobraćaja, a to su: izvorno-ciljni aerodromi, sa dominantnim saobraćajem od-tačke-do-tačke, i hub aerodromi, sa dominantnim transfernim saobraćajem za koji je karakteristično da se koncentriše u talase. Dodatno su analizirani i aerodromi na kojima postoje oba tipa saobraćaja. Rezultati disertacije pokazuju da se za izvorno-ciljne aerodrome može koristiti standardni pristup prilikom analize ukupnog kapaciteta vazdušne strane aerodroma, u kome se poletno-sletna staza i pristanišna platforma posmatraju odvojeno, pri čemu manji kapacitet nameće ograničenje ukupnog kapaciteta. Sa druge strane, u slučaju hub aerodroma kapacitet platforme i kapacitet poletno-sletne staze se ne mogu posmatrati nezavisno jedan od drugog. S tim u skladu, u ovoj doktorskoj disertaciji predložen je model za procenu kapaciteta platforme na hub aerodromima, koji pored konfiguracije platforme i strukture potražnje uzima u obzir i kapacitet poletno-sletne staze, kao i parametre koji opisuju talasnu strukturu saobraćaja...The thesis proposes an approach to analyzing the capacity of the existing (built) system under given physical and operational constraints and for given demand characteristics. The approach considers the linking of the (existing) runway capacity model with the (extended) apron capacity model, through the runway-apron functional relationship. The objective of the thesis was to evaluate and, if necessary, to modify/expand the existing apron capacity estimation models, as well as to define functional relationship between the runway system and apron(s). Existing apron capacity models are modified to include constraints on both aircraft classes and users (e.g. airlines), considering also different traffic types. The thesis also suggests apron capacity envelopes to illustrate sensitivity of apron capacity to changes in the demand structure with respect to dominant users, provided for a given apron configuration. Two general airport categories with respect to the role of the airport in the air transport network are analyzed: origin-destination airports (serving primarily point-to-point flights) and hub airports (serving primarily airline/alliance coordinated flights). Furthermore, the thesis also considers the co-existence of point-to-point and coordinated flights at a single airport. The results of the thesis show that the common approach in the overall airside capacity analysis can be applied at origin-destination airports: the runway system and apron(s) can be observed independently of each other, deriving the conclusion on the overall airside capacity by comparing the two. On the other hand, the finding of the thesis is that capacities of the runway system and apron(s) at the hub airports have to be observed linked to each other. Consequently, a model to estimate apron capacity at hub airport is offered in the thesis. In addition to apron configuration and demand structure it also takes into consideration: hubbing parameters and the runway system performance..

A Hybrid Tabu/Scatter Search Algorithm for Simulation-Based Optimization of Multi-Objective Runway Operations Scheduling

As air traffic continues to increase, air traffic flow management is becoming more challenging to effectively and efficiently utilize airport capacity without compromising safety, environmental and economic requirements. Since runways are often the primary limiting factor in airport capacity, runway operations scheduling emerge as an important problem to be solved to alleviate flight delays and air traffic congestion while reducing unnecessary fuel consumption and negative environmental impacts. However, even a moderately sized real-life runway operations scheduling problem tends to be too complex to be solved by analytical methods, where all mathematical models for this problem belong to the complexity class of NP-Hard in a strong sense due to combinatorial nature of the problem. Therefore, it is only possible to solve practical runway operations scheduling problem by making a large number of simplifications and assumptions in a deterministic context. As a result, most analytical models proposed in the literature suffer from too much abstraction, avoid uncertainties and, in turn, have little applicability in practice. On the other hand, simulation-based methods have the capability to characterize complex and stochastic real-life runway operations in detail, and to cope with several constraints and stakeholders’ preferences, which are commonly considered as important factors in practice. This dissertation proposes a simulation-based optimization (SbO) approach for multi-objective runway operations scheduling problem. The SbO approach utilizes a discrete-event simulation model for accounting for uncertain conditions, and an optimization component for finding the best known Pareto set of solutions. This approach explicitly considers uncertainty to decrease the real operational cost of the runway operations as well as fairness among aircraft as part of the optimization process. Due to the problem’s large, complex and unstructured search space, a hybrid Tabu/Scatter Search algorithm is developed to find solutions by using an elitist strategy to preserve non-dominated solutions, a dynamic update mechanism to produce high-quality solutions and a rebuilding strategy to promote solution diversity. The proposed algorithm is applied to bi-objective (i.e., maximizing runway utilization and fairness) runway operations schedule optimization as the optimization component of the SbO framework, where the developed simulation model acts as an external function evaluator. To the best of our knowledge, this is the first SbO approach that explicitly considers uncertainties in the development of schedules for runway operations as well as considers fairness as a secondary objective. In addition, computational experiments are conducted using real-life datasets for a major US airport to demonstrate that the proposed approach is effective and computationally tractable in a practical sense. In the experimental design, statistical design of experiments method is employed to analyze the impacts of parameters on the simulation as well as on the optimization component’s performance, and to identify the appropriate parameter levels. The results show that the implementation of the proposed SbO approach provides operational benefits when compared to First-Come-First-Served (FCFS) and deterministic approaches without compromising schedule fairness. It is also shown that proposed algorithm is capable of generating a set of solutions that represent the inherent trade-offs between the objectives that are considered. The proposed decision-making algorithm might be used as part of decision support tools to aid air traffic controllers in solving the real-life runway operations scheduling problem

A review of asset management literature on multi-asset systems

This article gives an overview of the literature on asset management for multi-unit systems with an emphasis on two multi-asset categories: fleet (a system of homogeneous assets) and portfolio (a system of heterogeneous assets). As asset systems become more complicated, researchers have employed different terms to refer to their specific problems. With an objective to facilitate readers in searching conducive studies to their interests, this paper establishes a novel classification scheme for multi-unit systems in accordance with essential features such as diversity of assets and intervention options. Moreover, discerning differences in characteristics between cross-component and cross-asset interactions, we select three types of potential multi-component dependencies (performance, stochastic, and resource) and extend their notions to be applicable to multi-asset systems. The investigation into these dependencies enables the identification of problems that could exist in real industrial settings but are yet to be determined in academia. Ultimately, we delve into modelling approaches adopted by previous researchers. This comprehensive information allows us to offer the insights into the current trends in multi-asset maintenance. We expect that the output of this review paper will not only stress research gaps on multi-asset systems, but more importantly help systematise future studies on this aspect

Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation

[EN] The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033, RED2018-102642-T), the SEPIE Erasmus+Program (2019-I-ES01-KA103-062602), and the IoF2020-H2020 (731884) project.Do C. Martins, L.; Tordecilla, RD.; Castaneda, J.; Juan-Pérez, ÁA.; Faulin, J. (2021). Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation. Energies. 14(16):1-30. https://doi.org/10.3390/en14165131130141

System-of-Systems Considerations in the Notional Development of a Metropolitan Aerial Transportation System

There are substantial future challenges related to sustaining and improving efficient, cost-effective, and environmentally friendly transportation options for urban regions. Over the past several decades there has been a worldwide trend towards increasing urbanization of society. Accompanying this urbanization are increasing surface transportation infrastructure costs and, despite public infrastructure investments, increasing surface transportation "gridlock." In addition to this global urbanization trend, there has been a substantial increase in concern regarding energy sustainability, fossil fuel emissions, and the potential implications of global climate change. A recently completed study investigated the feasibility of an aviation solution for future urban transportation (refs. 1, 2). Such an aerial transportation system could ideally address some of the above noted concerns related to urbanization, transportation gridlock, and fossil fuel emissions (ref. 3). A metro/regional aerial transportation system could also provide enhanced transportation flexibility to accommodate extraordinary events such as surface (rail/road) transportation network disruptions and emergency/disaster relief responses