Waste collection routing-limited multiple landfills and heterogeneous fleet

This article deals with a real-life waste collection routing problem. To efficiently plan waste collection, large municipalities may be partitioned into convenient sectors and only then can routing problems be solved in each sector. Three diverse situations are described, resulting in three different new models. In the first situation, there is a single point of waste disposal from where the vehicles depart and to where they return. The vehicle fleet comprises three types of collection vehicles. In the second, the garage does not match any of the points of disposal. The vehicle is unique and the points of disposal (landfills or transfer stations) may have limitations in terms of the number of visits per day. In the third situation, disposal points are multiple (they do not coincide with the garage), they are limited in the number of visits, and the fleet is composed of two types of vehicles. Computational results based not only on instances adapted from the literature but also on real cases are presented and analyzed. In particular, the results also show the effectiveness of combining sectorization and routing to solve waste collection problems.

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

Transporte internacional rodoviário de mercadorias: projecto de optimização operacional

No âmbito do estágio curricular realizado na DSV Transitários, surgiu a oportunidade de estar inserida em duas das áreas funcionais da empresa: durante o primeiro mês, no departamento comercial e nos restantes meses no departamento ROAD (rodoviário Internacional) no qual me foi proporcionado a oportunidade de desempenhar funções de Operacional de Tráfego Rodoviário Internacional. Desta forma, surge o desafio de integrar na equipa de operacionais ROAD da DSV, por forma a contribuir ativamente para a rotina da empresa e paralelamente analisar os processos operacionais do departamento, bem como, identificar todos os pontos que necessitem de melhoria. Após estar inserida neste sector, compreendi que a grupagem de mercadorias desempenha um papel fundamental neste departamento, na medida em que, quando desenvolvida de uma forma eficiente, pode traduzir-se numa atividade de extremo valor. A dinâmica diária desta atividade exige que os operadores de tráfego respondam de uma forma rápida e flexível aos problemas, apresentando soluções eficazes às solicitações do mercado. Para isso, é importante encontrar mecanismos capazes de os auxiliar na tomada decisões operacionais.

Sectors and routes in solid waste collection

Collecting and transporting solid waste is a constant problem for municipalities and populations in general. Waste management should take into account the preservation of the environment and the reduction of costs. The goal with this paper is to address a real-life solid waste problem. The case reveals some general and specific characteristics which are not rare, but are not widely addressed in the literature. Furthermore, new methods and models to deal with sectorization and routing are introduced, which can be extended to other applications. Sectorization and routing are tackled following a two-phase approach. In the first phase, a new method is described for sectorization based on electromagnetism and Coulomb’s Law. The second phase addresses the routing problems in each sector. The paper addresses not only territorial division, but also the frequency with which waste is collected, which is a critical issue in these types of applications. Special characteristics related to the number and type of deposition points were also a motivation for this work. A new model for a Mixed Capacitated Arc Routing Problem with Limited Multi-Landfills is proposed and tested in real instances. The computational results achieved confirm the effectiveness of the entire approach.

Sectorization: measures and an electromagnetism based approach

Sectorization means dividing a set of basic units into sectors or parts, a procedure that occurs in several contexts, such as political, health and school districting, social networks and sales territory or airspace assignment, to achieve some goal or to facilitate an activity. This presentation will focus on three main issues: Measures, a new approach to sectorization problems and an application in waste collection. When designing or comparing sectors different characteristics are usually taken into account. Some are commonly used, and they are related to the concepts of contiguity, equilibrium and compactness. These fundamental characteristics will be addressed, by defining new generic measures and by proposing a new measure, desirability, connected with the idea of preference. A new approach to sectorization inspired in Coulomb’s Law, which establishes a relation of force between electrically charged points, will be proposed. A charged point represents a small region with specific characteristics/values creating relations of attraction/repulsion with the others (two by two), proportional to the charges and inversely proportional to their distance. Finally, a real case about sectorization and vehicle routing in solid waste collection will be mentioned.

Recolha de resíduos sólidos urbanos - otimização de rotas

Este trabalho dá a conhecer um novo problema, Problema Capacitado de Rotas em Arcos Misto, com Múltiplos Aterros Limitados. Baseado na situação de recolha/transporte de Resíduos Sólidos Urbanos no concelho de Monção, são apresentadas características que, não sendo únicas em Portugal, nunca foram mencionadas na literatura. Diferencia-se pela existência de diversos pontos de deposição que, especialmente devido às reduzidas dimensões, apresentam restrições relacionadas com o número de visitas recebidas por dia. Um novo modelo de otimização, baseado na formulação do Mixed Ca- pacitated Arc Routing Problem é apresentado. São incluídos resultados computacionais provenientes de instâncias adaptadas da literatura e do problema real descrito.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Life Cycle Assessment of the Hybrid Vehicle – Toyota Prius

Die Luftverschmutzung, die globale Erwärmung sowie die Verknappung der endlichen Ressourcen sind die größten Bedenken der vergangenen Jahrzehnte. Die Nachfrage nach jeglicher Mobilität steigt rapide. Dementsprechend bemüht ist die Automobilindustrie Lösungen für Mobilität unter dem Aspekt der Nachhaltigkeit und dem Umweltschutz anzubieten. Die Elektrifizierung hat sich hierbei als der beste Weg herausgestellt, um die Umweltprobleme sowie die Abhängigkeit von fossilen Brennstoffen zu lösen. Diese Arbeit soll einen Einblick über die Umweltauswirkungen des Hybridfahrzeuges Toyota Prius geben. Hierbei findet eine Gliederung in vier verschiedene Lebensphasen statt. Im Anschluss bietet die Sachbilanz die Möglichkeit die Umweltauswirkungen mit verschiedenen Antriebsmöglichkeiten und Brennstoffen zu vergleichen. Das Modell hat gezeigt, dass der Toyota Prius während der Nutzung einen hohen Einfluss auf das Treibhauspotenzial aufweist. Durch die Nutzung anderer Brennstoffe, wie beispielsweise Ethanol oder Methanol lassen sich die Auswirkungen am Treibhauspotenzial sowie der Verbrauch an abiotischen Ressourcen reduzieren. Vergleicht man die Elektromobilität mit der konventionellen, so ist festzustellen, dass diese Art der Mobilität die derzeit beste Möglichkeit zur Reduzierung der Umweltbelastungen bietet. Die Auswirkungen der Elektromobilität sind im hohen Maße abhängig von der Art des verwendeten Strommixes.

Evaluating vehicle painting plans in an automobile assembly plant using an integrated AHP-PROMETHEE approach

The painting activity is one of the most complex and important activities in automobile manufacturing. The inherent complexity of the painting activity and the frequent need for repainting usually turn the painting process into a bottleneck in automobile assembly plants, which is reflected in higher operating costs and longer overall cycle times. One possible approach for optimizing the performance of the paint shop is to improve the efficiency of the color planning. This can be accomplished by evaluating the relative merits of a set of vehicle painting plans. Since this problem has a multicriteria nature, we resort to the multicriteria decision analysis (MCDA) methodology to tackle it. A recent trend in the MCDA field is the development of hybrid approaches that are used to achieve operational synergies between different methods. Here we apply, for the first time, an integrated approach that combines the strengths of the analytic hierarchy process (AHP) and the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), aided by Geometrical Analysis for Interactive Aid (GAIA), to the problem of assessing alternative vehicle painting plans. The management of the assembly plant found the results of value and is currently using them in order to schedule the painting activities such that an enhancement of the operational efficiency of the paint shop is obtained. This efficiency gain has allowed the management to bid for a new automobile model to be assembled at this specific plant.