A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Technical and mapping support for marine spatial planning: Final report

Washington depends on a healthy coastal and marine ecosystem to maintain a thriving economy and vibrant communities. These ecosystems support critical habitats for wildlife and a growing number of often competing ocean activities, such as fishing, transportation, aquaculture, recreation, and energy production. Planners, policy makers and resource managers are being challenged to sustainably balance ocean uses, and environmental conservation in a finite space and with limited information. This balancing act can be supported by spatial planning. Marine spatial planning (MSP) is a planning process that enables integrated, forward looking, and consistent decision making on the human uses of the oceans and coasts. It can improve marine resource management by planning for human uses in locations that reduce conflict, increase certainty, and support a balance among social, economic, and ecological benefits we receive from ocean resources. In March 2010, the Washington state legislature enacted a marine spatial planning law (RCW §43.372) to address resource use conflicts in Washington waters. In 2011, a report to the legislature and a workshop on human use data provided guidance for the marine spatial planning process. The report outlines a set of recommendations for the State to effectively undertake marine spatial planning and this work plan will support some of these recommendations, such as: federal integration, regional coordination, developing mechanisms to integrate scientific and technical expertise, developing data standards, and accessing and sharing spatial data. In 2012 the Governor amended the existing law to focus funding on mapping and ecosystem assessments for Washington’s Pacific coast and the legislature provided $2.1 million in funds to begin marine spatial planning off Washington’s coast. The funds are appropriated through the Washington Department of Natural Resources Marine Resources Stewardship Account with coordination among the State Ocean Caucus, the four Coastal Treaty Tribes, four coastal Marine Resource Committees and the newly formed stakeholder body, the Washington Coastal Marine Advisory Council.

Travel behaviour applied in freight transportation using intelligent products

The route planning problem for an order in freight transportation involves the selection of the best route for its transportation given a set of options that the network can offer. In its adaptive (or dynamic) version, the problem deals with the planning of a new route for an order while it is actually in transit typically because part or all of its pre-selected route is blocked or disrupted. In the intelligent product approach we are proposing, an order would be capable of identifying and evaluating such new routes in an automated manner and choosing the most preferable one without the intervention of humans. Because such approaches seek to mirror (and then automate) human decision making, in this paper we seek to identify new ways for dynamic route planning in industrial logistics inspired by the way people make similar decisions about their journey when they travel in multi-modal networks. We propose a new simulation game as a methodological tool for capturing their travel behaviour and we use it in this study. The results show that a simulation game can be used for capturing strategies and tactics of travellers and that intelligent products can provide a proper platform for the usage of such strategies in freight logistics. © 2012 IEEE.

Personalized public transportation information

Thesis to obtain the Master of Science Degree in Computer Science and Engineering

Tactical Vehicle Routing Planning with Application to Milk Collection and Distribution

De nombreux problèmes pratiques qui se posent dans dans le domaine de la logistique, peuvent être modélisés comme des problèmes de tournées de véhicules. De façon générale, cette famille de problèmes implique la conception de routes, débutant et se terminant à un dépôt, qui sont utilisées pour distribuer des biens à un nombre de clients géographiquement dispersé dans un contexte où les coûts associés aux routes sont minimisés. Selon le type de problème, un ou plusieurs dépôts peuvent-être présents. Les problèmes de tournées de véhicules sont parmi les problèmes combinatoires les plus difficiles à résoudre. Dans cette thèse, nous étudions un problème d’optimisation combinatoire, appartenant aux classes des problèmes de tournées de véhicules, qui est liée au contexte des réseaux de transport. Nous introduisons un nouveau problème qui est principalement inspiré des activités de collecte de lait des fermes de production, et de la redistribution du produit collecté aux usines de transformation, pour la province de Québec. Deux variantes de ce problème sont considérées. La première, vise la conception d’un plan tactique de routage pour le problème de la collecte-redistribution de lait sur un horizon donné, en supposant que le niveau de la production au cours de l’horizon est fixé. La deuxième variante, vise à fournir un plan plus précis en tenant compte de la variation potentielle de niveau de production pouvant survenir au cours de l’horizon considéré. Dans la première partie de cette thèse, nous décrivons un algorithme exact pour la première variante du problème qui se caractérise par la présence de fenêtres de temps, plusieurs dépôts, et une flotte hétérogène de véhicules, et dont l’objectif est de minimiser le coût de routage. À cette fin, le problème est modélisé comme un problème multi-attributs de tournées de véhicules. L’algorithme exact est basé sur la génération de colonnes impliquant un algorithme de plus court chemin élémentaire avec contraintes de ressources. Dans la deuxième partie, nous concevons un algorithme exact pour résoudre la deuxième variante du problème. À cette fin, le problème est modélisé comme un problème de tournées de véhicules multi-périodes prenant en compte explicitement les variations potentielles du niveau de production sur un horizon donné. De nouvelles stratégies sont proposées pour résoudre le problème de plus court chemin élémentaire avec contraintes de ressources, impliquant dans ce cas une structure particulière étant donné la caractéristique multi-périodes du problème général. Pour résoudre des instances de taille réaliste dans des temps de calcul raisonnables, une approche de résolution de nature heuristique est requise. La troisième partie propose un algorithme de recherche adaptative à grands voisinages où de nombreuses nouvelles stratégies d’exploration et d’exploitation sont proposées pour améliorer la performances de l’algorithme proposé en termes de la qualité de la solution obtenue et du temps de calcul nécessaire.

Planning autonomous vehicles in the absence of speed lanes using an elastic strip

Planning of autonomous vehicles in the absence of speed lanes is a less-researched problem. However, it is an important step toward extending the possibility of autonomous vehicles to countries where speed lanes are not followed. The advantages of having nonlane-oriented traffic include larger traffic bandwidth and more overtaking, which are features that are highlighted when vehicles vary in terms of speed and size. In the most general case, the road would be filled with a complex grid of static obstacles and vehicles of varying speeds. The optimal travel plan consists of a set of maneuvers that enables a vehicle to avoid obstacles and to overtake vehicles in an optimal manner and, in turn, enable other vehicles to overtake. The desired characteristics of this planning scenario include near completeness and near optimality in real time with an unstructured environment, with vehicles essentially displaying a high degree of cooperation and enabling every possible(safe) overtaking procedure to be completed as soon as possible. Challenges addressed in this paper include a (fast) method for initial path generation using an elastic strip, (re-)defining the notion of completeness specific to the problem, and inducing the notion of cooperation in the elastic strip. Using this approach, vehicular behaviors of overtaking, cooperation, vehicle following,obstacle avoidance, etc., are demonstrated.

Constructive heuristic algorithm for the DC model in network transmission expansion planning

A novel constructive heuristic algorithm to the network expansion planning problem is presented the basic idea comes from Garver's work applied to the transportation model, nevertheless the proposed algorithm is for the DC model. Tests results with most known systems in the literature are carried out to show the efficiency of the method.

Constructive heuristic algorithm in branch-and-bound structure applied to transmission network expansion planning

A constructive heuristic algorithm to solve the transmission system expansion planning problem is proposed with the aim of circumventing some critical problems of classical heuristic algorithms that employ relaxed mathematical models to calculate a sensitivity index that guides the circuit additions. The proposed heuristic algorithm is in a branch-and-bound algorithm structure, which can be used with any planning model, such as Transportation model, DC model, AC model or Hybrid models. Tests of the proposed algorithm are presented on real Brazilian systems.

Specialised branch-and-bound algorithm for transmission network expansion planning

An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

Test systems and mathematical models for transmission network expansion planning

The data of four networks that can be used in carrying out comparative studies with methods for transmission network expansion planning are given. These networks are of various types and different levels of complexity. The main mathematical formulations used in transmission expansion studies-transportation models, hybrid models, DC power flow models, and disjunctive models are also summarised and compared. The main algorithm families are reviewed-both analytical, combinatorial and heuristic approaches. Optimal solutions are not yet known for some of the four networks when more accurate models (e.g. The DC model) are used to represent the power flow equations-the state of the art with regard to this is also summarised. This should serve as a challenge to authors searching for new, more efficient methods.

A branch-and-bound algorithm for the multi-stage transmission expansion planning

This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.

Urban sprawl and energy use for transportation in the largest Brazilian cities

A study of the relationships between the amount of energy consumed for transportation purposes and a few selected variables related to urban form and socioeconomic characteristics of some of the largest Brazilian cities is conducted in this work. The studied cities include all 27 state capitals regardless of their size and population and 184 urban areas each with more than 20,000 inhabitants located in the state of São Paulo. Two different techniques were applied for data analyses: a more traditional regression analysis approach and artificial neural networks. In general, the results found in the analyses conducted here support the assumption that urban sprawl increases the energy use for transportation. In the case of the 27 state capitals, the analysis indicated that two spatial variables have a strong impact on the energy consumed for urban transportation: urban density and the ratio between the longest distances in the east-west and north-south directions. In the case of the 184 urbanized areas we also reached a similar conclusion. In that case, however, income and employment level apparently have a stronger influence on the amount of energy consumed. The results of the present study stress the importance of physical planning in developing country cities in order to reduce energy use for transportation. © 2007 International Energy Initiative, Inc.

Domain reduction using GRASP construction phase for transmission expansion planning problem

This paper proposes a new strategy to reduce the combinatorial search space of a mixed integer linear programming (MILP) problem. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) is employed to reduce the domain of the integer variables of the transportation model of the transmission expansion planning (TM-TEP) problem. This problem is a MILP and very difficult to solve specially for large scale systems. The branch and bound (BB) algorithm is used to solve the problem in both full and the reduced search space. The proposed method might be useful to reduce the search space of those kinds of MILP problems that a fast heuristic algorithm is available for finding local optimal solutions. The obtained results using some real test systems show the efficiency of the proposed method. © 2012 Springer-Verlag.

Sprawling and Urban transportation system: Impacts in the city of Londrina, Parana, Brazil

After nearly 80 years since the construction of its core, represented today by the city's central area, Londrina, located in the state of Parana, has the appearance of a new city but its features and trends of planning policies depict the bad examples of Brazilian cities. With a booming urban growth, from north to south of the county, the urban interstices represented by big voids in the middle of the city created speculation and the concept of an ideal city slowly disappeared. With a metropolitan appearance and, at the same time, with small town aspects, Londrina stands out as an automobile-oriented city, a fact that has impacted the livelihood of the population, generating environmental impacts for all social classes. This paper discusses how the form of occupation in Londrina, characterized by the sprawl phenomenon and its relation to car preference as a mode of transportation has generated urban environmental impacts. It was concluded that the choice of using cars in Londrina, as well in other medium-sized Brazilian cities studied by the comparative method, has increased and has generated bottlenecks in traffic. As a consequence, there is a constant expropriation of properties for widening roads and at the same time, the presence of various densities and urban voids that form an uneven urban space and an obstacle to efficient urban planning. © 2012 WIT Press.

Draft future work programme for Ad Hoc Working Group for Transportation Planners

Extrae del informe de consultor "An agenda for transport planning in the Caribbean" las sugerencias para el futuro programa de trabajo en relacion a las areas de actividad, modalidades para la implementacion del programa, aspectos financieros, y creacion de una Unidad de Investigacion de Transporte Multimodal.