Luis Filipe Caetano

Bio: Luis Filipe Caetano is an academic researcher from Instituto Superior Técnico. The author has contributed to research in topics: Track (rail transport) & Renewal theory. The author has an hindex of 5, co-authored 5 publications receiving 244 citations. Previous affiliations of Luis Filipe Caetano include Technical University of Lisbon.

Optimisation model to schedule railway track renewal operations: a life-cycle cost approach

Abstract: Besides high initial construction costs, ballasted railway tracks also have high investment requirements, related to maintenance and renewal (M&R) works. Decision support tools for railway track components that optimise these works are increasingly gaining in importance. This paper presents an optimisation model that integrates ballast, rail and sleeper degradation models in a mixed integer linear programming model. This model links the decisions to renew these components with their condition and takes advantage of the integrated planning of renewal works to minimise the railway track life-cycle cost (LCC). The practical utility of the model is illustrated with a case study involving the Portuguese Lisbon–Porto line. The results indicate a reduction in track renewal cost if the grouping of components, track segments and time interval for renewal operations are optimised. Furthermore, this paper demonstrates that possible annual budget restrictions for railway track M&R operations can have an important inf...

Availability Approach to Optimizing Railway Track Renewal Operations

Abstract: This paper proposes a multiobjective optimization approach for planning railway ballast, rail, and sleeper renewal operations. The objective is to support an informed decision that considers not only the railway track life-cycle cost (LCC) but also the track occupation times required to perform interventions. Two objective functions were minimized, as follows: (1) railway track unavailability caused by railway track maintenance and renewal operations, and (2) railway track components’ LCC. Furthermore, to rationalize the renewal strategy, the model considers a multicomponent formulation that assesses, in time and space, the opportunistic combination of railway track renewal activities. A numerical application of the model on a real case study (Lisbon-Oporto line) is developed and discussed. The results show the interest of using this simple multiobjective optimization approach to obtain a decision-making process to support the scheduling of major railway track renewal works with an informed LCC-un...

Predictive Maintenance Model for Ballast Tamping

Abstract: In order to optimally schedule railway track maintenance operations, it is essential to accurately estimate future track conditions. This study proposes a railway track geometry degradation model that considers uncertainties in the forecast by defining a track geometry reliability parameter. The degradation model is integrated in a multiobjective optimization approach to assess railway track maintenance strategies considering a cost–reliability trade off. Finally, a numerical application of the model to a real case study is presented. The results show the usefulness of the proposed approach to guarantee a required track geometry performance with effective maintenance investments.

Strategic Model to Optimize Railway-Track Renewal Operations at a Network Level

Abstract: This paper presents an optimization model for scheduling railway ballast, rail, and sleeper renewal operations at a network level. The objective of the model is to minimize the expected railway track life-cycle cost (LCC) and track unavailability costs derived from user impacts caused by traffic disruption during track renewal operations. To minimize costs, the model assesses the opportunistic renewal of railway track components and takes advantage of planning from a network perspective to study the possibility of reusing track components on different lines. The practical utility of the model is illustrated with a case study involving the Portuguese railway network. The results indicate that user costs have an important influence on decision making in the track renewal process and that the network perspective of renewal planning can reduce the direct costs of these operations.

A modeling framework for the dynamic management of free-floating bike-sharing systems

Abstract: Given the growing importance of bike-sharing systems nowadays, in this paper we suggest an alternative approach to mitigate the most crucial problem related to them: the imbalance of bicycles between zones owing to one-way trips. In particular, we focus on the emerging free-floating systems, where bikes can be delivered or picked-up almost everywhere in the network and not just at dedicated docking stations. We propose a new comprehensive dynamic bike redistribution methodology that starts from the prediction of the number and position of bikes over a system operating area and ends with a relocation Decision Support System. The relocation process is activated at constant gap times in order to carry out dynamic bike redistribution, mainly aimed at achieving a high degree of user satisfaction and keeping the vehicle repositioning costs as low as possible. An application to a test case study, together with a detailed sensitivity analysis, shows the effectiveness of the suggested novel methodology for the real-time management of the free-floating bike-sharing systems.

Bike-sharing stations: A maximal covering location approach

Abstract: The promotion of sustainable alternatives to motorized individual mobility has been seen in the past few decades as one of the cornerstones in a strategy to reduce the negative externalities related to the transportation sector. Bicycle sharing is increasingly popular as a sustainable transport system and the number of bike sharing schemes has grown significantly worldwide in recent years. One of the most important elements in implementation of these systems is the location of the stations. In fact the non-optimal locating of bike sharing compromises its success. Municipalities or public–private partnerships are mostly responsible for implementing bike-sharing schemes. The public investment in bicycle mobility (particularly bike-sharing) is complex because it is always subject to a budget. The main concern for public investment is to maximize the benefits through the design and implementation of bike-sharing systems. This work sets out a methodology to help with the decision-making of bike-sharing systems. The research work we present proposes using an optimization method to design the bike sharing system such that it maximizes the demand covered and takes the available budget as a constraint. It combines strategic decisions for locating bike-sharing stations and defining the dimension of the system (stations and number of bicycles) with operational decisions (relocating bicycles). As an outcome, the model determines the optimal location of the bicycle stations, the fleet size, the capacity of the stations and the number of bicycles in each station, considering an initial investment lower than the given budget. In addition, it balances the annual cost of the system and the revenue assuming a possible supplementary budget from the system provider to cover any loss resulting from the shortfall between its operating cost and the revenue from the subscription charges. A case study in Coimbra, Portugal, is presented and discussed.

Solving a static repositioning problem in bike-sharing systems using iterated tabu search

Abstract: In this paper, we study the static bike repositioning problem where the problem consists of selecting a subset of stations to visit, sequencing them, and determining the pick-up/drop-off quantities (associated with each of the visited stations) under the various operational constraints. The objective is to minimize the total penalties incurred at all the stations. We present an iterated tabu search heuristic to solve the described problem. Experimental results show that this simple heuristic can generate high quality solutions using small computing times.

Data analysis and optimization for (citi)bike sharing

Abstract: Bike-sharing systems are becoming increasingly prevalent in urban environments. They provide a low-cost, environmentally-friendly transportation alternative for cities. The management of these systems gives rise to many optimization problems. Chief among these problems is the issue of bicycle rebalancing. Users imbalance the system by creating demand in an asymmetric pattern. This necessitates action to put the system back in balance with the requisite levels of bicycles at each station to facilitate future use. In this paper, we tackle the problem of maintaing system balance during peak rush-hour usage as well as rebalancing overnight to prepare the system for rush-hour usage. We provide novel problem formulations that have been motivated by both a close collaboration with the New York City bike share (Citibike) and a careful analysis of system usage data. We analyze system data to discover the best placement of bikes to facilitate usage. We solve routing problems for overnight shifts as well as clustering problems for handling mid rush-hour usage. The tools developed from this research are currently in daily use at NYC Bike Share LLC, operators of Citibike.