Some propositions to find optimal conditions to simulate a flexible transport using an Agent-Based Model

This paper presents a method to assess the sensitivity of a flexible transport model based on agents and simulated using NetLogo. We simulate and we analyse a set of 124 transportation scenarios on several virtual networks and we assess their performance. Our main objective is to detect thresholds in the system scalability and efficiency. The research leads to three main results: (i) using Agent-Based Model, it is possible to significantly improve the global transport efficiency without any general objective function, (ii) there exists an optimal balance between the demand frequency and the number of simulated agents to simulate and perform a good flexible transport, (ii) to some extent, the network topological structure plays a non-negligible role in transport efficiency

Vehicle Routing Problems with Fuel Consumption and Stochastic Travel Speeds

Conventional vehicle routing problems (VRP) always assume that the vehicle travel speed is fixed or time-dependent on arcs. However, due to the uncertainty of weather, traffic conditions, and other random factors, it is not appropriate to set travel speeds to fixed constants in advance. Consequently, we propose a mathematic model for calculating expected fuel consumption and fixed vehicle cost where average speed is assumed to obey normal distribution on each arc which is more realistic than the existing model. For small-scaled problems, we make a linear transformation and solve them by existing solver CPLEX, while, for large-scaled problems, an improved simulated annealing (ISA) algorithm is constructed. Finally, instances from real road networks of England are performed with the ISA algorithm. Computational results show that our ISA algorithm performs well in a reasonable amount of time. We also find that when taking stochastic speeds into consideration, the fuel consumption is always larger than that with fixed speed model

Optimization of occupancy rate in dial-a-ride problems via linear fractional column generation

International audienceIn this paper, we consider a dial-a-ride problem where the objective is to maximize the passenger occupancy rate. The problem arises from an on-demand transportation system developed in a rural zone in France, where the objective of encouraging people meeting is pursued. We address the solution of the problem with a column generation approach, applied to a set partitioning formulation where the objective function is fractional. Based on the literature on linear fractional programming, two methods are developed to deal with this fractional objective. Experiments permit to compare these two approaches and to evaluate the impact of the new objective compared to a standard min-cost or min-time optimization

New Formulations and Solution Methods for the Dial-a-ride Problem

The classic Dial-A-Ride Problem (DARP) aims at designing the minimum-cost routing solution that accommodates a set of user requests under constraints at the operations planning level. It is a highly constrained combinatorial optimization problem initially designed for providing door-to-door transportation for people with limited mobility (e.g. the elderly or disabled). It consists of routing and scheduling a fleet of capacitated vehicles to service a set of requests with specified pickup and drop-off locations and time windows. With the details of requests obtained either beforehand (static DARP) or en-route (dynamic DARP), dial-a-ride operators strive to deliver efficient and yet high-quality transport services that satisfy each passenger's individual travel needs. The goal of this thesis is threefold: (1) to propose rich DARP formulations where users' preferences are taken into account, in order to improve service quality of Demand-Responsive Transport (DRT) services and promote ridership strategically; (2) to develop novel and efficient solution methods where local search, column generation, metaheuristics and machine learning techniques are integrated to solve large-scale DARPs; and (3) to conduct real-life DARP case studies (using data extracted from NYC Yellow Taxi trip records) to test the practicality of proposed models and solution methods, as well as to emphasise the importance of connecting algorithms with real-world datasets. These aims are achieved and presented in the three core chapters of this thesis. In the first core chapter (Chapter 3), two Mixed Integer Programming (MIP) formulations (link-based and path-based) of DARP are presented, alongside with their objective functions and standard solution methods. This chapter builds the foundation of the thesis by elaborating the base models and algorithms that this thesis is based on, and by running benchmark experiments and reporting numerical results as the base line of the whole thesis. In the second core chapter (Chapter 4), two DARP models (one deterministic, one stochastic) integrated with users' preferences from dial-a-ride service operators' perspective are proposed, facilitating them to optimise their overall profit while maintaining service quality. In these models, users' utility users' preferences are considered within a dial-a-ride problem. A customized local search based heuristic and a matheuristic are developed to solve the proposed Chance-Constrained DARP (CC-DARP). Numerical results are reported for both DARP benchmark instances and a realistic case study based on New York City yellow taxi trip data. This chapter also explores the design of revenue/fleet management and pricing differentiation. The proposed chance-constrained DARP formulation provides a new decision-support tool to inform on revenue and fleet management, including fleet sizing, for DRT systems at a strategic planning level. In the last core chapter (Chapter 5), three hybrid metaheuristic algorithms integrated with Reinforcement Learning (RL) techniques are proposed and implemented, aiming to increase the scale-up capability of existing DARP solution methods. Machine learning techniques and/or a branching scheme are incorporated with various metaheuristic algorithms including VNS and LNS, providing innovative methodologies to solve large-instance DARPs in a more efficient manner. Thompson Sampling (TS) is applied to model dual values of requests under a column generation setting to negate the effect of dual oscillation (i.e. promote faster converging). The performance of proposed algorithms is tested benchmark datasets, and strengths and weaknesses across different algorithms are reported

Ferramenta de suporte ao projeto de sistemas flexíveis de transporte público de passageiros

Tese de Doutoramento em Engenharia Industrial e de Sistemas.As áreas rurais, com densidades populacionais baixas, apresentam desafios à mobilidade das suas populações. Os serviços de transporte público regular têm-se mostrado ineficazes e ineficientes levando os operadores de transporte coletivo a reduzir a sua oferta e a diminuir a qualidade do serviço oferecido. Em alternativa aos serviços regulares de transporte, alguns estudos têm vindo a mostrar as vantagens da implementação de sistemas de transportes flexíveis, em particular, transportes a pedido (DRT - Demand Responsive Transport). No entanto, os principais resultados observados nos estudos realizados apontam para a existência de várias dificuldades para o sucesso dos DRTs (aspetos legais, organizacionais, financeiros, etc.), assim como para a inexistência de ferramentas de apoio capazes de auxiliar os decisores nas etapas do planeamento estratégico e tático, antes mesmo de proceder à sua implementação. No sentido de minorar ou colmatar as lacunas referidas, esta tese pretende contribuir para uma discussão abrangente destes sistemas de transporte e propor uma nova ferramenta de suporte ao projeto de sistemas DRT. A ferramenta proposta integra um sistema de apoio à decisão (SAD) concebido para estimar o desempenho operacional de diferentes configurações a implementar, permitindo optar pela melhor solução encontrada. O SAD é suportado por um modelo de simulação microscópica do funcionamento do sistema, e inclui métodos de solução para diferentes variantes do problema de otimização de rotas e escalas encontradas neste tipo de serviços de transporte, para além de uma framework para a avaliação da sustentabilidade das soluções. Na validação do SAD desenvolvido, utilizou-se um estudo de caso português. Os resultados dos testes efetuados permitiram evidenciar as potencialidades da ferramenta proposta. Adicionalmente, a avaliação da sustentabilidade da solução permitiu identificar a difícil sustentabilidade financeira deste tipo de sistemas, mas também as suas vantagens em termos sociais e ambientais que poderão justificar a sua adoção.Rural areas with low population densities, present challenges to mobility of their populations. The regular public transport services have proved quite ineffective and inefficient leading transport operators to reduce their supply and their services quality. As an alternative to regular services, some studies have come to show the advantages of the implementation of flexible transport systems, as demand responsive transport (DRT). However, the main results obtained in the studies scope point both to the existence of different types of difficulties to the DRTs success (legal, organizational, financial aspects, etc.), and the lack of supporting tools that can assist decision makers in both strategic and tactical planning, even before proceeding to implement. In order to overcome these shortcomings, this thesis intends to discuss broadly these transport systems and to present a new tool to support the design of DRT systems. The proposed tool integrates a decision support system (DSS) specifically designed to assess the operating performance of different alternative system configurations to be implemented, allowing to choose the best solution found. The DSS is supported by a microscopic simulation model of the system operation, and even includes solution methods for different variants of the vehicle routing problem found in this type of transportation services, furthermore a framework to evaluate the solutions sustainability. To validate the developed DSS, we used a Portuguese case study. The test results allowed highlighting the DSS potentialities. Additionally, the solution sustainability assessment identified the hard financial self-sustaining of this type of systems, but also their advantages in both social and environmental impact that will probably be sufficient to justify its implementation.Fundação para a Ciência e Tecnologia SFRH/BD/60776/2009