A two-stage route optimization algorithm for light aircraft transport systems

This paper presents a route optimization algorithm for light aircraft operating under visual flight rules. The problem aims at finding a minimum-duration, collision-free route in three spatial dimensions with possible aircraft maneuvers. The optimal route takes into account the aircraft kinodynamic characteristics and its interaction with external wind. A data processing approach is presented to recast the flying environment as a series of polyhedrons based on which a mixed-integer linear model is formulated. A two-stage route optimization model is then introduced to solve real-life instances. Computational experiments depict the efficiency of this approach.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Logistic

Electrification of a bus system with fast charging stations: Impact of battery degradation on design decisions

In this paper, we evaluate the cost of the electrification of an existing bus network. We propose a family of bi-objective mathematical models to demonstrate the trade-off between strategic (i.e., battery sizing and the locations of charging stations) and operational decisions (i.e., battery degradation). The proposed mathematical models investigate different charging policies and measure their impacts on overall cost. Battery degradation is estimated by a tailored and linearized semi-empirical approach and is explicitly incorporated in the proposed mixed-integer linear models. The impact of different charging policies on reducing the overall costs is evaluated for a bus network in Rotterdam. The results show that allowing for flexibility in the loss of energy levels at each bus cycle results in savings up to 17% in battery aging.Transport and PlanningTransport and Logistic

A Time-use Model for the Automated Vehicle-era

Automated Vehicles (AVs) offer their users a possibility to perform new non-driving activities while being on the way. The effects of this opportunity on travel choices and travel demand have mostly been conceptualised and modelled via a reduced penalty associated with (in-vehicle) travel time. This approach invariably leads to a prediction of more car-travel. However, we argue that reductions in the size of the travel time penalty are only a crude proxy for the variety of changes in time-use and travel patterns that are likely to occur at the advent of AVs. For example, performing activities in an AV can save time and in this way enable the execution of other activities within a day. Activities in an AV may also eliminate or generate a need for some other activities and travel. This may lead to an increase, or decrease in travel time, depending on the traveller’s preferences, schedule, and local accessibility. Neglecting these dynamics is likely to bias forecasts of travel demand and travel behaviour in the AV-era. In this paper, we present an optimisation model which rigorously captures the time-use effects of travellers’ ability to perform on-board activities. Using a series of worked out examples, we test the face validity of the model and demonstrate how it can be used to predict travel choices in the AV-era

Preference-based facility location for on-demand logistics

In the context of on-demand logistics systems, the facility location is becoming even more critical as demand characteristics and customer preferences are changing with respect to the location, time, customer segments etc. Classic facility location models do not take into account customer preferences when the set of facility locations are optimized and therefore the expected profit of the classic facility location models is not an accurate representation of reality. This paper develops a preference-based facility location model which incorporates customer preferences while maximizing the system-wide expected profit in the context of an on-demand logistics provider. The customers are first segmented based on historical data and segment specific preferences are estimated by logit mixture where we take into account heterogeneity within the segment. The performance of the preference-based facility location model is measured by total expected profit and consumer surplus. It is found that, the preference-based facility location model is not only a more accurate representation of reality but also has the potential to increase the expected profit compared to typical facility location models.Accepted Author ManuscriptTransport Engineering and LogisticsTransport and Logistic

The Impact of Collaborative Scheduling and Routing for Interconnected Logistics: A European Case Study

Interconnected logistics system can play an important role towards having a more sustainable green freight transport. Recently, after introducing the concept of Physical Internet (PI), researchers have started to explore the opportunities and challenges that a collaborative and interconnected network could create in different aspects of the supply chain. In this research, we study the last mile delivery as well as vehicle dispatching problems under the assumptions of collaborative supply chain networks while assuming that modularized boxes are applied inside the network from the provider to the final customer. Our research aims at proposing a more efficient resource planning with the minimal number of empty vehicle movements running on roads that ultimately leads to decrease carbon dioxide emission. The assumptions have been tested and verified using real data coming from a major retail company in Europe

Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems

Traffic congestion is uncertain and undesirable in logistics and leads to arrival uncertainty at downstream locations engendering disruptions. This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. Due to the recent advancements in cyber-physical systems, we propose an adaptive system that uses the real-time truck Estimated Time of Arrival (ETA) data to make informed decisions. We develop an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. We developed a simulation model of the adaptive system and reported the estimated benefits from our initial experiments.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and LogisticsTransport and Plannin

Theoretical test for the work "Hinterland freight transportation replanning model under the framework of synchromodality".

We build a replanning model for hinterland freight transportation. To test the difficulties of solving the model, we test it with more theoretical cases. The dataset is shared on this open platform for the reviewer and readers to check

An integrated territory planning and vehicle routing approach for a multi-objective residential waste collection problem

In this paper, we address a multi-objective residential waste collection problem with an integrated territory planning and vehicle routing approach. Dividing the problem into territories enables drivers to carry out the same route every week so they get familiar with it and residents put out their bins at the appropriate time. Another benefit is to reduce the computation time for large problems, since the complex characteristics of the involved vehicle routing problem make it otherwise difficult to solve. There are three characteristics that are important for good territory planning: minimum overlap, minimum travel time, and balanced workload. The purpose of this paper is to investigate the influence these three objectives have on each other, since they might be contradictory. Moreover, an Adaptive Large Neighborhood Search (ALNS) algorithm is developed for this specific problem which uses a K-means algorithm to generate the initial solution for territories. The results with the three objectives are shown to be useful for planners seeking to make informed decisions through the trade-off across different solutions with the Pareto frontiers provided. Moreover, the ALNS algorithm is shown to find good quality solutions in a reasonable computational time.Transport and LogisticsTransport Engineering and Logistic

Hinterland freight transportation replanning model under the framework of synchromodality

Hinterland freight transportation is managed according to a pre-designed schedule. In daily operations, unexpected uncertainties cause deviation from the original plan. Thus replanning is needed to deal with the perturbations and complete the transportation tasks. This paper proposes a mixed-integer programming model to re-plan hinterland freight transportation, based on the framework of synchromodality. It is a holistic resolution of shipment flow rerouting, consequence transshipment organization in the intermediate terminals, and corresponding service rescheduling. The replanning benefits from a high operational flexibility and coordination via a split of shipment and aligning the departure time of service flows with the shipment flows.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and LogisticsTransport and Plannin

Passenger-centric timetable rescheduling: A user equilibrium approach

Unexpected disruptions commonly occur in the railway network, causing delays, and extra cost for operators and inconvenience for passengers by missing their connection and facing overcrowded trains. This paper presents a passenger-centric approach for timetable rescheduling in case of disruption. We study a railway system in which passengers are free to choose their itinerary and compete over limited train capacity. We explicitly model the passengers’ decisions using a choice model. We propose a multi-objective algorithmic approach to solve the problem. Service punctuality, operating cost, and passengers’ inconvenience are selected as objectives. Computational experiments are performed on the Swiss and Dutch railway networks. The results demonstrate the performance of the algorithm in finding high-quality solutions in a computationally efficient manner.Transport and LogisticsTransport and Plannin