What drives the Rebound Effect in transportation? An evaluation based on a Traveling Purchaser Problem

Limiting climate change is one of the most important challenges of the 21st century. Focusing on the transport sector, encouraging the use of more energy-efficient transport modes, and improving the performance of vehicles are the main targets in the fight for GHG reductions. However, due to Rebound Effect (RE), it is proven that improvements in engine fuel efficiency result in lower cost per kilometer driven and can induce individuals to use vehicles more often or to drive longer distances. As a result, the potential energy savings from improved energy efficiency could be partially or totally offset. Therefore, we decided to examine "What drives the Rebound Effect in transportation". To answer this research question, a Traveling Purchaser Problem was evaluated. This simple real-life business application models a situation in which a company owns one or several vehicles and has to buy specific products. The goal is to select and visit a subset of suppliers to satisfy a given demand for each product while minimizing both purchasing and travel costs. In total, 510 instances of this problem with various characteristics and parameters were generated and solved using the optimization software AIMMS. The impact of five main experimentations was deeply investigated. In addition, the trends obtained from these experiments were confirmed by fitting a logistic regression and a decision tree. The results of the various experiments showed that four variables can influence the occurrence of RE in a transportation network. On the one hand, RE tended to increase with the number of potential suppliers from which the firm can choose and the number of vehicles that the company owns to procure the products. On the other hand, the exclusivity of the products to source, as well as the introduction of a distance-traveled tax, reduced the occurrence of RE. To sum up, significant conclusions could be drawn from the experiments and the results can be easily transferred to real-life business applications. Recommendations for possible future studies were also discussed.nhhma

A multi-parent genetic algorithm for solving longitude–latitude-based 4D traveling salesman problems under uncertainty

In this study, we propose a mathematical model of a 4D clustered traveling salesman problem (CTSP) to address the cost-effective security and risk-related difficulties associated with the TSP. We used a multiparent-based memetic genetic algorithm to optimize paths between all clusters and proposed unique heuristic approaches to create clusters and reconnect them. We constructed a 4D CTSP considering multiple routes between two locations and multiple available vehicles on each route. Travel expenses and risks impact every itinerary; however, the behaviors of these costs and risks are always uncertain. We inspected various standard benchmark problems from (TSPLIB) using the proposed calculations. Real-life problems in the tourism industry motivate a longitude–latitude-based CTSP with risk constraints. Thus, we determined the risk of each path based on longitude and latitude. The contributions of this study are twofold: developing a genetic algorithm and heuristics based on mathematical modeling of a real problem.</p

Desenvolvimento de uma heurística para a determinação de rotas de recolha e distribuição de produtos considerando múltiplos veículos

Trabalho de projecto de mestrado, Matemática Aplicada à Economia e Gestão, Universidade de Lisboa, Faculdade de Ciências, 2019Neste projeto, apresenta-se um problema de determinação de rotas de recolha e distribuição com escolha seletiva de mercados. Existe uma frota homogénea de veículos e existem pontos onde se faz a recolha de determinados produtos e, posteriormente, faz-se a distribuição pelos clientes, tendo estes uma dada procura que tem que ser satisfeita. Não é obrigatório visitar todos os pontos de recolha disponíveis. O objetivo é construir rotas para os veículos que partam de um depósito, passem por certos mercados para comprar os produtos, entreguem os produtos aos clientes e regressem ao depósito, de modo a minimizar a soma dos custos de aquisição dos produtos e dos custos de deslocação. Neste trabalho, faz-se uma breve referência a alguns problemas de determinação de rotas para veículos e à sua aplicação a casos reais. Apresenta-se, ainda, um modelo matemático em programação linear inteira mista. Desenvolve-se, para obter soluções admissíveis para este problema, uma heurística que é constituída por duas fases. A primeira fase consiste em criar rotas com um único cliente e com os mercados que o servem, tendo como base uma heurística desenvolvida para resolver o Travelling Purchaser Problem. Nesta primeira fase, constrói-se uma solução inicial, a qual é melhorada através de dois procedimentos: Market drop e Market exchange. A segunda fase consiste na fusão das rotas obtidas, juntando vários clientes na mesma rota, de modo a diminuir os custos de viagem. Os resultados computacionais são obtidos para dados gerados aleatoriamente, considerando duas áreas onde estão os clientes, o depósito e os mercados, dois tipos de probabilidade associados à existência de determinado produto em cada mercado e à probabilidade de a procura de determinado produto por parte de um cliente ser superior a zero e diferentes valores para número de mercados e procura. Fazse uma análise dos resultados obtidos em termos de média das melhorias percentuais quando se faz a fusão de rotas e em termos de tempos computacionais, considerando duas capacidades diferentes para os veículos.In this project, a pickup and delivery problem with selective choice of markets is presented. There is a fleet of homogenous vehicles which travels through pickup points to get certain products and then delivers them to the customers who have a certain demand that must be satisfied. It is not necessary to visit every available pickup point. The goal is to find a good, next to optimal, route for the vehicles that leave the depot, stop at certain markets where products are bought, deliver those products to the customers and then return to the depot, in order to minimize the sum of the purchasing costs and the travelling costs. In this project, a brief reference to some vehicle routing problems and some of its applications to the real world is made. A mixed integer linear programming model is presented. A heuristic is built to find feasible solutions for this problem. The heuristic consists of two phases, the first of which, consists of creating routes with a single customer and the markets which satisfy the customer’s demand. This phase is based on a heuristic for the Travelling Purchaser Problem where an initial feasible solution is found and improved upon through two procedures: Market Drop and Market Exchange. The second phase consists of merging the routes obtained beforehand, joining multiple customers in the same route, in order to decrease travelling costs. Some computational results were obtained for randomly generated data, considering two different areas for the depot, customers and markets, two different probabilities for the existence of a certain product in a certain market, two different probabilities for the existence of demand of a certain product for each customer and, lastly, different numbers of customers and markets. The results were analysed in regards to the average percentage improvements for the route merging, as well as regarding the computational time, considering two different maximum vehicle capacities

The family traveling salesman problem

Consider a depot, a partition of the set of nodes into subsets, called families, and a cost matrix. The objective of the family traveling salesman problem (FTSP) is to find the minimum cost circuit that starts and ends at the depot and visits a given number of nodes per family. The FTSP was motivated by the order picking problem in warehouses where products of the same type are stored in different places and it is a recent problem. Nevertheless, the FTSP is an extension of well-known problems, such as the traveling salesman problem. Since the benchmark instances available are in small number we developed a generator, which given a cost matrix creates an FTSP instance with the same cost matrix. We generated several test instances that are available in a site dedicated to the FTSP. We propose several mixed integer linear programming models for the FTSP. Additionally, we establish a theoretical and a practical comparison between them. Some of the proposed models have exponentially many constraints, therefore we developed a branch-and-cut (B&C) algorithm to solve them. With the B&C algorithm we were able to obtain the optimal value of open benchmark instances and of the majority of the generated instances. As the FTSP is an NP-hard problem we develop three distinct heuristic methods: a genetic algorithm, an iterated local search algorithm and a hybrid algorithm. With all of them we were able to improve the best upper bounds available in the literature for the benchmark instances that still have an unknown optimal value. We created a new variant of the FTSP, called the restricted family traveling salesman problem (RFTSP), in which nodes from the same family must be visited consecutively. We apply to the RFTSP the methods proposed for the FTSP and develop a new formulation based on the interfamily and the intrafamily relationship

Integrating Consumer Flexibility in Smart Grid and Mobility Systems - An Online Optimization and Online Mechanism Design Approach

Consumer flexibility may provide an important lever to align supply and demand in service systems. However, harnessing dispersed flexibility endowments in the presence of self-interested agents requires appropriate incentive structures. This thesis quantifies the potential value of consumers\u27 flexibility in smart grid and mobility systems. In order to include incentives, online optimization approaches are augmented with methods from online mechanism design

Management, Technology and Learning for Individuals, Organisations and Society in Turbulent Environments

This book presents the collection of fifty two papers which were presented on the First International Conference on BUSINESS SUSTAINABILITY ’08 - Management, Technology and Learning for Individuals, Organisations and Society in Turbulent Environments, held in Ofir, Portugal, from 25th to 27th of June, 2008. The main motive of the meeting was the growing awareness of the importance of the sustainability issue. This importance had emerged from the growing uncertainty of the market behaviour that leads to the characterization of the market, i.e. environment, as turbulent. Actually, the characterization of the environment as uncertain and turbulent reflects the fact that the traditional technocratic and/or socio-technical approaches cannot effectively and efficiently lead with the present situation. In other words, the rise of the sustainability issue means the quest for new instruments to deal with uncertainty and/or turbulence. The sustainability issue has a complex nature and solutions are sought in a wide range of domains and instruments to achieve and manage it. The domains range from environmental sustainability (referring to natural environment) through organisational and business sustainability towards social sustainability. Concerning the instruments for sustainability, they range from traditional engineering and management methodologies towards “soft” instruments such as knowledge, learning, creativity. The papers in this book address virtually whole sustainability problems space in a greater or lesser extent. However, although the uncertainty and/or turbulence, or in other words the dynamic properties, come from coupling of management, technology, learning, individuals, organisations and society, meaning that everything is at the same time effect and cause, we wanted to put the emphasis on business with the intention to address primarily the companies and their businesses. From this reason, the main title of the book is “Business Sustainability” but with the approach of coupling Management, Technology and Learning for individuals, organisations and society in Turbulent Environments. Concerning the First International Conference on BUSINESS SUSTAINABILITY, its particularity was that it had served primarily as a learning environment in which the papers published in this book were the ground for further individual and collective growth in understanding and perception of sustainability and capacity for building new instruments for business sustainability. In that respect, the methodology of the conference work was basically dialogical, meaning promoting dialog on the papers, but also including formal paper presentations. In this way, the conference presented a rich space for satisfying different authors’ and participants’ needs. Additionally, promoting the widest and global learning environment and participativeness, the Conference Organisation provided the broadcasting over Internet of the Conference sessions, dialogical and formal presentations, for all authors’ and participants’ institutions, as an innovative Conference feature. In these terms, this book could also be understood as a complementary instrument to the Conference authors’ and participants’, but also to the wider readerships’ interested in the sustainability issues. The book brought together 97 authors from 10 countries, namely from Australia, Finland, France, Germany, Ireland, Portugal, Russia, Serbia, Sweden and United Kingdom. The authors “ranged” from senior and renowned scientists to young researchers providing a rich and learning environment. At the end, the editors hope and would like that this book will be useful, meeting the expectation of the authors and wider readership and serving for enhancing the individual and collective learning, and to incentive further scientific development and creation of new papers. Also, the editors would use this opportunity to announce the intention to continue with new editions of the conference and subsequent editions of accompanying books on the subject of BUSINESS SUSTAINABILITY, the second of which is planned for year 2011.info:eu-repo/semantics/publishedVersio

Social informatics

5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013, Proceedings</p