Operational research IO 2021—analytics for a better world. XXI Congress of APDIO, Figueira da Foz, Portugal, November 7–8, 2021

This book provides the current status of research on the application of OR methods to solve emerging and relevant operations management problems. Each chapter is a selected contribution of the IO2021 - XXI Congress of APDIO, the Portuguese Association of Operational Research, held in Figueira da Foz from 7 to 8 November 2021. Under the theme of analytics for a better world, the book presents interesting results and applications of OR cutting-edge methods and techniques to various real-world problems. Of particular importance are works applying nonlinear, multi-objective optimization, hybrid heuristics, multicriteria decision analysis, data envelopment analysis, simulation, clustering techniques and decision support systems, in different areas such as supply chain management, production planning and scheduling, logistics, energy, telecommunications, finance and health. All chapters were carefully reviewed by the members of the scientific program committee.info:eu-repo/semantics/publishedVersio

National freight transport planning: towards a Strategic Planning Extranet Decision Support System (SPEDSS)

This thesis provides a `proof-of-concept' prototype and a design architecture for a Object Oriented (00) database towards the development of a Decision Support System (DSS) for the national freight transport planning problem. Both governments and industry require a Strategic Planning Extranet Decision Support System (SPEDSS) for their effective management of the national Freight Transport Networks (FTN). This thesis addresses the three key problems for the development of a SPEDSS to facilitate national strategic freight planning: 1) scope and scale of data available and required; 2) scope and scale of existing models; and 3) construction of the software. The research approach taken embodies systems thinking and includes the use of: Object Oriented Analysis and Design (OOA/D) for problem encapsulation and database design; artificial neural network (and proposed rule extraction) for knowledge acquisition of the United States FTN data set; and an iterative Object Oriented (00) software design for the development of a `proof-of-concept' prototype. The research findings demonstrate that an 00 approach along with the use of 00 methodologies and technologies coupled with artificial neural networks (ANNs) offers a robust and flexible methodology for the analysis of the FTN problem domain and the design architecture of an Extranet based SPEDSS. The objectives of this research were to: 1) identify and analyse current problems and proposed solutions facing industry and governments in strategic transportation planning; 2) determine the functional requirements of an FTN SPEDSS; 3) perform a feasibility analysis for building a FTN SPEDSS `proof-of-concept' prototype and (00) database design; 4) develop a methodology for a national `internet-enabled' SPEDSS model and database; 5) construct a `proof-of-concept' prototype for a SPEDSS encapsulating identified user requirements; 6) develop a methodology to resolve the issue of the scale of data and data knowledge acquisition which would act as the `intelligence' within a SPDSS; 7) implement the data methodology using Artificial Neural Networks (ANNs) towards the validation of it; and 8) make recommendations for national freight transportation strategic planning and further research required to fulfil the needs of governments and industry. This thesis includes: an 00 database design for encapsulation of the FTN; an `internet-enabled' Dynamic Modelling Methodology (DMM) for the virtual modelling of the FTNs; a Unified Modelling Language (UML) `proof-of-concept' prototype; and conclusions and recommendations for further collaborative research are identified

A flexible metaheuristic framework for solving rich vehicle routing problems

Route planning is one of the most studied research topics in the operations research area. While the standard vehicle routing problem (VRP) is the classical problem formulation, additional requirements arising from practical scenarios such as time windows or vehicle compartments are covered in a wide range of so-called rich VRPs. Many solution algorithms for various VRP variants have been developed over time as well, especially within the class of so-called metaheuristics. In practice, routing software must be tailored to the business rules and planning problems of a specific company to provide valuable decision support. This also concerns the embedded solution methods of such decision support systems. Yet, publications dealing with flexibility and customization of VRP heuristics are rare. To fill this gap this thesis describes the design of a flexible framework to facilitate and accelerate the development of custom metaheuristics for the solution of a broad range of rich VRPs. The first part of the thesis provides background information to the reader on the field of vehicle routing problems and on metaheuristic solution methods - the most common and widely-used solution methods to solve VRPs. Specifically, emphasis is put on methods based on local search (for intensification of the search) and large neighborhood search (for diversification of the search), which are combined to hybrid methods and which are the foundation of the proposed framework. Then, the main part elaborates on the concepts and the design of the metaheuristic VRP framework. The framework fulfills requirements of flexibility, simplicity, accuracy, and speed, enforcing the structuring and standardization of the development process and enabling the reuse of code. Essentially, it provides a library of well-known and accepted heuristics for the standard VRP together with a set of mechanisms to adapt these heuristics to specific VRPs. Heuristics and adaptation mechanisms such as templates for user-definable checking functions are explained on a pseudocode level first, and the most relevant classes of a reference implementation using the Microsoft .NET framework are presented afterwards. Finally, the third part of the thesis demonstrates the use of the framework for developing problem-specific solution methods by exemplifying specific customizations for five rich VRPs with diverse characteristics, namely the VRP with time windows, the VRP with compartments, the split delivery VRP, the periodic VRP, and the truck and trailer routing problem. These adaptations refer to data structures and neighborhood search methods and can serve as a source of inspiration to the reader when designing algorithms for new, so far unstudied VRPs. Computational results are presented to show the effectiveness and efficiency of the proposed framework and methods, which are competitive with current state-of-the-art solvers of the literature. Special attention is given to the overall robustness of heuristics, which is an important aspect for practical application

Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Comunicações veiculares híbridas

Vehicle Communications is a promising research field, with a great potential for the development of new applications capable of improving road safety, traffic efficiency, as well as passenger comfort and infotainment. Vehicle communication technologies can be short-range, such as ETSI ITS-G5 or the 5G PC5 sidelink channel, or long-range, using the cellular network (LTE or 5G). However, none of the technologies alone can support the expected variety of applications for a large number of vehicles, nor all the temporal and spatial requirements of connected and autonomous vehicles. Thus, it is proposed the collaborative or hybrid use of short-range communications, with lower latency, and of long-range technologies, potentially with higher latency, but integrating aggregated data of wider geographic scope. In this context, this work presents a hybrid vehicle communications model, capable of providing connectivity through two Radio Access Technologies (RAT), namely, ETSI ITS-G5 and LTE, to increase the probability of message delivery and, consequently, achieving a more robust, efficient and secure vehicle communication system. The implementation of short-range communication channels is done using Raw Packet Sockets, while the cellular connection is established using the Advanced Messaging Queuing Protocol (AMQP) protocol. The main contribution of this dissertation focuses on the design, implementation and evaluation of a Hybrid Routing Sublayer, capable of isolating messages that are formed/decoded from transmission/reception processes. This layer is, therefore, capable of managing traffic coming/destined to the application layer of intelligent transport systems (ITS), adapting and passing ITS messages between the highest layers of the protocol stack and the available radio access technologies. The Hybrid Routing Sublayer also reduces the financial costs due to the use of cellular communications and increases the efficiency of the use of the available electromagnetic spectrum, by introducing a cellular link controller using a Beacon Detector, which takes informed decisions related to the need to connect to a cellular network, according to different scenarios. The experimental results prove that hybrid vehicular communications meet the requirements of cooperative intelligent transport systems, by taking advantage of the benefits of both communication technologies. When evaluated independently, the ITS-G5 technology has obvious advantages in terms of latency over the LTE technology, while the LTE technology performs better than ITS-G5, in terms of throughput and reliability.As Comunicações Veiculares são um campo de pesquisa promissor, com um grande potencial de desenvolvimento de novas aplicações capazes de melhorar a segurança nas estradas, a eficiência do tráfego, bem com o conforto e entretenimento dos passageiros. As tecnologias de comunicação veícular podem ser de curto alcance, como por exemplo ETSI ITS-G5 ou o canal PC5 do 5G, ou de longo alcance, recorrendo à rede celular (LTE ou 5G). No entanto, nenhuma das tecnologias por si só, consegue suportar a variedade expectável de aplicações para um número de veículos elevado nem tampouco todos os requisitos temporais e espaciais dos veículos conectados e autónomos. Assim, é proposto o uso colaborativo ou híbrido de comunicações de curto alcance, com latências menores, e de tecnologias de longo alcance, potencialmente com maiores latências, mas integrando dados agregados de maior abrangência geográfica. Neste contexto, este trabalho apresenta um modelo de comunicações veiculares híbrido, capaz de fornecer conectividade por meio de duas Tecnologias de Acesso por Rádio (RAT), a saber, ETSI ITS-G5 e LTE, para aumentar a probabilidade de entrega de mensagens e, consequentemente, alcançar um sistema de comunicação veicular mais robusto, eficiente e seguro. A implementação de canais de comunicação de curto alcance é feita usando Raw Packet Sockets, enquanto que a ligação celular é estabelecida usando o protocolo Advanced Messaging Queuing Protocol (AMQP). A contribuição principal desta dissertação foca-se no projeto, implementação e avaliação de uma sub camada hibrída de encaminhamento, capaz de isolar mensagens que se formam/descodificam a partir de processos de transmissão/receção. Esta camadada é, portanto, capaz de gerir o tráfego proveniente/destinado à camada de aplicação de sistemas inteligentes de transportes (ITS) adaptando e passando mensagens ITS entre as camadas mais altas da pilha protocolar e as tecnologias de acesso rádio disponíveis. A sub camada hibrída de encaminhamento também potencia uma redução dos custos financeiros devidos ao uso de comunicações celulares e aumenta a eficiência do uso do espectro electromagnético disponível, ao introduzir um múdulo controlador da ligação celular, utilizando um Beacon Detector, que toma decisões informadas relacionadas com a necessidade de uma conexão a uma rede celular, de acordo com diferentes cenários. Os resultados experimentais comprovam que as comunicações veículares híbridas cumprem os requisitos dos sistemas cooperativos de transporte inteligentes, ao tirarem partido das vantagens de ambas tecnologias de comunicação. Quando avaliadas de forma independente, constata-se que que a tecnologia ITS-G5 tem vantagens evidentes em termos de latência sobre a tecnologia LTE, enquanto que a tecnologia LTE tem melhor desempenho que a LTE, ai nível de débito e fiabilidade.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

AIRO 2016. 46th Annual Conference of the Italian Operational Research Society. Emerging Advances in Logistics Systems Trieste, September 6-9, 2016 - Abstracts Book

The AIRO 2016 book of abstract collects the contributions from the conference participants. The AIRO 2016 Conference is a special occasion for the Italian Operations Research community, as AIRO annual conferences turn 46th edition in 2016. To reflect this special occasion, the Programme and Organizing Committee, chaired by Walter Ukovich, prepared a high quality Scientific Programme including the first initiative of AIRO Young, the new AIRO poster section that aims to promote the work of students, PhD students, and Postdocs with an interest in Operations Research. The Scientific Programme of the Conference offers a broad spectrum of contributions covering the variety of OR topics and research areas with an emphasis on “Emerging Advances in Logistics Systems”. The event aims at stimulating integration of existing methods and systems, fostering communication amongst different research groups, and laying the foundations for OR integrated research projects in the next decade. Distinct thematic sections follow the AIRO 2016 days starting by initial presentation of the objectives and features of the Conference. In addition three invited internationally known speakers will present Plenary Lectures, by Gianni Di Pillo, Frédéric Semet e Stefan Nickel, gathering AIRO 2016 participants together to offer key presentations on the latest advances and developments in OR’s research

A Quantitative Framework for Assessing Vulnerability and Redundancy of Freight Transportation Networks

Freight transportation networks are an important component of everyday life in modern society. Disruption to these networks can make peoples’ daily lives extremely difficult as well as seriously cripple economic productivity. This dissertation develops a quantitative framework for assessing vulnerability and redundancy of freight transportation networks. The framework consists of three major contributions: (1) a two- stage approach for estimating a statewide truck origin-destination (O-D) trip table, (2) a decision support tool for assessing vulnerability of freight transportation networks, and (3) a quantitative approach for measuring redundancy of freight transportation networks.The dissertation first proposes a two-stage approach to estimate a statewide truck O-D trip table. The proposed approach is supported by two sequential stages: the first stage estimates a commodity-based truck O-D trip table using the commodity flows derived from the Freight Analysis Framework (FAF) database, and the second stage uses the path flow estimator (PFE) concept to refine the truck trip table obtained from the first stage using the truck counts from the statewide truck count program. The model allows great flexibility of incorporating data at different spatial levels for estimating the truck O- D trip table. The results from the second stage provide us a better understanding of truck flows on the statewide truck routes and corridors, and allow us to better manage the anticipated impacts caused by network disruptions.A decision support tool is developed to facilitate the decision making system through the application of its database management capabilities, graphical user interface, GIS-based visualization, and transportation network vulnerability analysis. The vulnerability assessment focuses on evaluating the statewide truck-freight bottlenecks/chokepoints. This dissertation proposes two quantitative measures: O-D connectivity (or detour route) in terms of distance and freight flow pattern change in terms of vehicle miles traveled (VMT). The case study adopts a “what-if” analysis approach by generating the disruption scenarios of the structurally deficient bridges in Utah due to earthquakes. In addition, the potential impacts of disruptions to multiple bridges in both rural and urban areas are evaluated and compared to the single bridge failure scenarios.This dissertation also proposes an approach to measure the redundancy of freight transportation networks based on two main dimensions: route diversity and network spare capacity. The route diversity dimension is used to evaluate the existence of multiple efficient routes available for users or the degree of connections between a specific O-D pair. The network spare capacity dimension is used to quantify the network- wide spare capacity with an explicit consideration of congestion effect. These two dimensions can complement each other by providing a two-dimensional characterization of freight transportation network redundancy. Case studies of the Utah statewide transportation network and coal multimodal network are conducted to demonstrate the features of the vulnerability and redundancy measures and the applicability of the quantitative assessment methodology