594 research outputs found
A multiobjective model for optimizing bus lines design considering pollution generation
No full textThis article presents a multiobjective optimization model for the Bus Network Design Problem which simmulteneaously optimizes the passengers demand covered by the network, the total travel time and the generated pollution. Preliminary tests were performed in a simulated instance of the city of Montevideo, showing that the model is able to nd different solutions that consider different trade-off among objectives.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Facultad de Ingeniería; UruguayFil: Toutouh, Jamal. Computer Science And Artificial Intelligence Laboratory; Estados Unidos1st International Workshop on Advanced Information and Computation Technologies and SystemsIrkutskRusiaMatrosov Institute for System Dynamics and Control Theor
Soft computing methods for multiobjective location of garbage accumulation points in smart cities
No full textThis article describes the application of soft computing methods for solving the problem of locating garbage accumulation points in urban scenarios. This is a relevant problem in modern smart cities, in order to reduce negative environmental and social impacts in the waste management process, and also to optimize the available budget from the city administration to install waste bins. A specific problem model is presented, which accounts for reducing the investment costs, enhance the number of citizens served by the installed bins, and the accessibility to the system. A family of single- and multi-objective heuristics based on the PageRank method and two mutiobjective evolutionary algorithms are proposed. Experimental evaluation performed on real scenarios on the cities of Montevideo (Uruguay) and Bahía Blanca (Argentina) demonstrates the effectiveness of the proposed approaches. The methods allow computing plannings with different trade-off between the problem objectives. The computed results improve over the current planning in Montevideo and provide a reasonable budget cost and quality of service for Bahía Blanca.Fil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados UnidosFil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; Urugua
Exact and heuristic approaches for multi-objective garbage accumulation points location in real scenarios
Get PDFMunicipal solid waste management is a major challenge for nowadays urban societies, because it accounts for a large proportion of public budget and, when mishandled, it can lead to environmental and social problems. This work focuses on the problem of locating waste bins in an urban area, which is considered to have a strong influence in the overall efficiency of the reverse logistic chain. This article contributes with an exact multiobjective approach to solve the waste bin location in which the optimization criteria that are considered are: the accessibility to the system (as quality of service measure), the investment cost, and the required frequency of waste removal from the bins (as a proxy of the posterior routing costs). In this approach, different methods to obtain the objectives ideal and nadir values over the Pareto front are proposed and compared. Then, a family of heuristic methods based on the PageRank algorithm is proposed which aims to optimize the accessibility to the system, the amount of collected waste and the installation cost. The experimental evaluation was performed on real-world scenarios of the cities of Montevideo, Uruguay, and Bahía Blanca, Argentina. The obtained results show the competitiveness of the proposed approaches for constructing a set of candidate solutions that considers the different trade-offs between the optimization criteria.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Toutouh, Jamal. Computer Science And Artificial Intelligence Laboratory; Estados UnidosFil: Nesmachnow, Sergio. Facultad de Ingeniería; Urugua
A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
No full textPower supply is one of the basic needs in modern smart homes. Computer-aid tools help optimizing energy utilization, contributing to sustainable goals of modern societies. For this purpose, this article presents a mathematical formulation to the household energy planning problem and a specic resolution method to build schedules for using deferrable electric that can reduce the cost of the electricity bill while keeping user satisfaction at a satisfactory level. User satisfaction have a great variability, since it is based on human preferences, thus a stochastic simulation-optimization approach is applied for handling uncertainty in the optimization process. Results over instances based on real-world data show the competitiveness of the proposed approach, which is able to compute dierent compromise solution accounting for the trade-off between these two conficting optimization criteria.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados UnidosFil: Luna, Francisco. Universidad de Málaga; EspañaInternational Conference of Production Research - Americas 2020Bahía BlancaArgentinaUniversidad Nacional del Su
Multiobjective design of sustainable public transportation systems
Get PDFThe design of the bus network is a complex problem in modern cities, since different conflicting objectives have to be considered, from both the perspective of bus companies and the citizens. This article presents a multiobjective model for designing a sustainable public transportation network that simultaneously optimizes the covered travel demands by passengers, the total travel time, and the generated pollution. The proposed model is solved using exact weighted sum and a heuristic procedure based on the standard shortest path problem. Preliminary tests were performed in small real-world instances of Montevideo, Uruguay. Experiments allowed obtaining a set of compromising solutions that in turn allow exploring different trade-off among the optimization criteria. The proposed heuristic was competitive, being able to find a good compromising solution in short computing times.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados Unidos1st International Workshop on Advanced Information and Computation Technologies and SystemsIrkutskRusiaMatrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Science
An explicit evolutionary approach for multiobjective energy consumption planning considering user preferences in smart homes
Get PDFModern Smart Cities are highly dependent on an efficient energy service since electricity is used in an increasing number of urban activities. In this regard, Time-of-Use prices for electricity is a widely implemented policy that has been successful to balance electricity consumption along the day and, thus, diminish the stress and risk of shortcuts of electric grids in peak hours. Indeed, residential customers may now schedule the use of deferrable electrical appliances in their smart homes in off-peak hours to reduce the electricity bill. In this context, this work aims to develop an automatic planning tool that accounts for minimizing the electricity costs and enhancing user satisfaction, allowing them to make more efficient usage of the energy consumed. The household energy consumption planning problem is addressed with a multiobjective evolutionary algorithm, for which problem-specific operators are devised, and a set of state-of-the-art greedy algorithms aim to optimize different criteria. The proposed resolution algorithms are tested over a set of realistic instances built using real-world energy consumption data, Time-of-Use prices from an electricity company, and user preferences estimated from historical information and sensor data. The results show that the evolutionary algorithm is able to improve upon the greedy algorithms both in terms of the electricity costs and user satisfaction and largely outperforms to a large extent the current strategy without planning implemented by users.Fil: Nesmachnow, Sergio. Facultad de Ingeniería; UruguayFil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Toutouh, Jamal. Massachusetts Institute of Technology. Science And Artificial Intelligence Laboratory; Estados UnidosFil: Luna, Francisco. Universidad de Málaga.
Instituto de Tecnologías e Ingeniería del Software; Españ
The Benefits of Being Economics Professor A (and not Z)
Get PDFAlphabetic name ordering on multi-authored academic papers, which is the convention in the economics discipline and various other disciplines, is to the advantage of people whose last name initials are placed early in the alphabet. As it turns out, Professor A, who has been a first author more often than Professor Z, will have published more articles and experienced afaster growth rate over the course of her career as a result of reputation and visibility. Moreover, authors know that name ordering matters and indeed take ordering seriously: Several characteristics of an author group composition determine the decision to deviate from the default alphabetic name order to a significant extent.performance measurement, incentives, economists, name ordering
Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
Get PDFIn the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Toutouh, Jamal. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; EspañaFil: Luna, Francisco. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; Españ
Exploring new innovation in e-learning / Jamal Othman
Get PDFAlhamdulillah, the fourth edition of ebook under SIG of e-Learning@CS has been successfully published. Representing the editorial board, I want to express my appreciation to all authors for their participation in this e-book edition. I wish to express my sincere appreciation to Madam Norazah Umar, the Program Coordinator for the Department of Computer and Mathematical Sciences (JSKM) who has given words of encouragement in making this publication a reality. Starting from 2022, the committee of SIG e-Learning@CS has decided to publish this eBook twice a year. This e-book will be published in April and October each year following the evaluation period of MyATP 2.0 system. The fourth edition of the e-book focuses on innovation in teaching. The authors are encouraged to share experiences and ideas that have been applied and implemented since the Open Distance Learning (ODL) approach was introduced during Movement Controls Orders (MCO). A total of 16 papers have been submitted by JSKM lecturers and varieties of teaching innovations have been elaborated and well explained by the author
Un modelo bi-objetivo de programación entera para localizar puntos de acumulación de residuos: un estudio de caso
Get PDFAumentar la eficiencia en la gestión de los Residuos Sólidos Urbanos (RSU) es crucial para los gobiernos municipales, que son los que generalmente se encargan de la recolección, ya que esta actividad consume un porcentaje importante de sus recursos presupuestarios. La incorporación de herramientas de apoyo a la toma de decisiones puede contribuir a mejorar el sistema de gestión de RSU, especialmente reduciendo los costos de inversión requeridos. Este artículo propone una formulación metemática, basada en programación entera, para determinar la localización de puntos de acumulación de residuos minimizando los costos del sistema, incluyendo tanto el costo de instalación de los contenedores como la cantidad de visitas necesarias del vehículo de recolección, lo cual está relacionado con los costos de la logística de recolección. El modelo se aplicó en un conjunto de escenarios reales de una importante ciudad argentina que todavía utiliza un sistema de puerta a puerta, incluyendo tanto intancias que donde los residuos son recolectados sin clasficar, como actualmente se realiza en esta ciudad, como instancias que incorporan la clasificación en origen de los mismos. A pesar de que los escenarios con clasificación en origen resultaron más desafiantes para el algoritmo de resolución propuesto, se obtuvieron un conjunto de soluciones factibles para todos los escenarios planteados. Estas soluciones pueden ser utilizadas como un punto inicial para migrar desde un sistema de puerta a puerta a uno de contenedores comunitarios.Enhancing efficiency in Municipal Solid Waste (MSW) management is crucial for local governments, which are generally in charge of collection, since this activity explains a large proportion of their budgetary expenses. The incorporation of decision support tools can contribute to improve the MSW system, specially by reducing the required investment of funds. This article proposes a mathematical formulation, based on integer programming, to determine the location of garbage accumulation points while minimizing the expenses of the system, i.e., the installment cost of bins and the required number of visits the collection vehicle which is related with the routing cost of the collection. The model was tested in some scenarios of an important Argentinian city that stills has a door-to-door system, including instances with unsorted waste, which is the current situation of the city, and also instances with source classified waste. Although the scenarios with classified waste evidenced to be more challenging for the proposed resolution approach, a set of solutions was provided in all scenarios. These solutions can be used as a starting point for migrating from the current door-to-door system to a community bins system.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados Unido
- …
