Integer linear programming formulation of the vehicle positioning problem in automated manufacturing systems

8 páginasThis paper addresses the problem of vehicle location (positioning) for automated transport in fully automated manufacturing systems. This study is motivated by the complexity of vehicle control found in modern integrated circuit semiconductor fabrication facilities where the material handling network path is composed of multiple loops interconnected. In order to contribute to decrease the manufacturing lead-time of semiconductor products, we propose an integer linear program that minimizes the maximum time needed to serve a transport request. Computation experiments are based on real-life data. We discuss the practical usefulness of the mathematical model by means of a simulation experiment used to analyze the factory operational behavio

SISTEMAS DE INFORMACIÓN Y TOMA DE DECISIONES METODOLOGÍA PARA LA PROGRAMACIÓN DE HORARIOS Y SALONES DE CLASES UNIVERSITARIAS – UN CASO DE ESTUDIO

Universidades, y en general instituciones de educación en todos los niveles, enfrentan en cada periodo académico el problema de la programación de horarios y la asignación de aulas (salones) de clase. En la literatura académica, este problema es una caracterización del problema de timetabling (Hernández et al. 2008). Puesto que existen recursos limitados en infraestructura y medios educativos, el problema consiste en asignar salones (aulas de clases) y recursos (docentes, equipos de apoyo, etc.) a un grupo de clases que deben tomar los estudiantes de acuerdo con su programa de estudios. Otras definiciones recientes del problema se encuentran en los trabajos de Schaerf (1999), Burke y Petrovic (2002) y Pillay (2013). La solución requiere la satisfacción de restricciones fuertes (duras) y suaves. De manera general, se requiere que las clases, módulos o eventos asociados sean programados en espacios horarios de tal forma que, primero, los estudiantes tengan cierta flexibilidad en la escogencia de los cursos; segundo, que los profesores y docentes tengan asignados sus cursos en espacios horarios que les permitan realizar otras actividades (gestión académica, investigación, etc.); y tercero, que la infraestructura sea utilizada de la mejor manera posible. Por esta razón, se invierte mucho tiempo en la planeación y asignación de estos recursos, con el fin de aprovechar al máximo la capacidad instalada. A pesar de los avances en el diseño de procedimientos formales (computacionales) para la resolución del problema, no existe evidencia en la literatura de que estos avances tomen en cuenta restricciones reales o hayan sido efectivamente traducidos en implementaciones reales en las universidades (McCollum 2007). En un estudio realizado hace más de 10 años, Carter y Laporte (1998) manifestaron haberse “sorprendido al descubrir que hay muy pocos artículos sobre planeación o programación de horarios de clases que reportan una real utilización de los métodos empleados en la investigación” [traducción de los autores]. El estudio de McCollum (2007) reporta las mismas conclusiones. 1 Una de las estrategias para reducir este distanciamiento entre los desarrollos teóricos y la implementación real en las universidades de los modelos y algoritmos de programación de horarios consiste en resaltar la importancia de los aspectos particulares de cada institución educativa (McCullan 2007). Bajo esta premisa, el objetivo de este artículo es presentar el impacto que se obtiene al diseñar modelos de optimización apropiados para la programación de horarios en la Universidad de La Sabana, Colombia. Para lograrlo, la siguiente sección presenta en detalle la metodología empleada. Posteriormente se presenta la caracterización del problema, así como los resultados obtenidos. Finalmente, el artículo presenta las conclusiones y algunas líneas para trabajo futuro

Short- and mid-term evaluation of the use of electric vehicles in urban freight transport collaborative networks: a case study

Despite its negative impacts, freight transportation is a primary component of all supply chains. Decision makers have considered diverse strategies, such as Horizontal Collaboration (HC) and the usage of alternative types of vehicles, to reduce overall cost and the related environmental and social impacts. This paper assesses the implementation of an electric fleet of vehicles in urban goods distribution under HC strategy between carriers. A biased randomisation based algorithm is used to solve the problem with a multi-objective function to explore the relationships between both delivery and environmental costs. Real data from the city of Bogota, Colombia are used to validate this approach. Experiments with different costs and demands projections are performed to analyse short- and medium-term impacts related to the usage of electric vehicles in collaborative networks. Results show that the optimal selection of vehicle types depends considerably on the time horizon evaluation and demand variation.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT) and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Special Patrimonial Fund from Universidad de La Sabana (Colombia) and the doctoral grant from the UOC-Open University of Catalonia (Spain)

Minimización del tiempo total de flujo de tareas en una sola máquina: Estado del arte

La programación de operaciones en una sola máquina es un problema clásico de la investigación de operaciones. Numerosos métodos han sido propuestos para resolver diferentes instancias del problema, dependiendo de las restricciones impuestas y del objetivo del mismo. En este artículo estamos interesados en ilustrar el estado actual de desarrollo de los métodos y algoritmos existentes en la literatura para el problema de minimización del flujo total de tareas sujetas a fechas de llegadas, tanto en problemas estáticos como dinámicos. Además, las posibilidades de trabajo y las preguntas abiertas serán igualmente expuestas

Simulation-based optimization approach for vehicle allocation in a private transport service: A case study

Poor urban planning and traffic congestion lead to excessive delays in workers’ transit times and decrease their quality of life, especially in emerging countries. Several medium and large companies have a need to hire a transport service for their staff. In this type of transportation system, there is a heterogeneous fleet of vehicles, which are assigned to a set of predefined routes. However, the total transport delay can be even greater if the private transportation system is inefficient or not controlled. The approach proposed in this study seeks to optimize the private transport service by defining the best allocation of its fleet to its routes. A mathematical model is proposed to minimize user wait times. This approach is validated using real data obtained from a transport company in Co-lombia. The results demonstrate the quantitative benefits that can be achieved when the proposed approach is implemented, represented by a considerable reduction in user wait times

The location routing problem with facility sizing decisions

The location routing problem (LRP) integrates operational decisions on vehicle routing operations with strategic decisions on the location of the facilities or depots from which the distribution will take place. In other words, it combines the well-known vehicle routing problem (VRP) with the facility location problem (FLP). Hence, the LRP is an NP-hard combinatorial optimization problem, which justifies the use of metaheuristic approaches whenever large-scale instances need to be solved. In this paper, we explore a realistic version of the LRP in which facilities of different capacities are considered, i.e., the manager has to consider not only the location but also the size of the facilities to open. In order to tackle this optimization problem, three mixed-integer linear formulations are proposed and compared. As expected, they have been proved to be cost- and time- inefficient. Hence, a biased-randomized iterated local search algorithm is proposed. Classical instances for the LRP with homogeneous facilities are naturally extended to test the performance of our approach.Peer ReviewedPostprint (published version

Breaking Frontiers and Barriers in Engineering: Education, Research and Practice

Abstract This paper focuses on the problem of line balancing in an assembly line. Although there are numerous studies published on the various aspects of the problem, most of the work focuses on the single-model problem, while the number of studies on the mixed-model assembly line balancing problem assume that processing times of tasks are deterministic. Task time variation however has a great impact with short cycle times. So, because there is always some variation when performing tasks, our research addresses stochastic processing duration of tasks. We propose an analytical analysis of the problem by using a multi-objective mathematical formulation that aims to minimize the total number of stations, to maximize system's productivity and to find a production sequence that smoothes system's operation

Combining heuristics with simulation and fuzzy logic to solve a flexible-size location routing problem under uncertainty

The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.This work has been partially supported by the Spanish Ministry of Science (PID2019-111100RB-C21/AEI/10.13039/501100011033). In addition, it has received the support of the Doctoral School at the Universitat Oberta de Catalunya (Spain) and the Universidad de La Sabana (INGPhD-12-2020).Peer ReviewedPostprint (published version

Operations research as a decision-making tool in the health sector: A state of the art

The contributions of Operations Research (OR) in the healthcare field have been extensively studied in the scientific literature since the 1960s, covering decision support tools with operational, tactical, and strategic approaches. The aim of this article is to analyze the historical development of the application of OR models in healthcare. The application trends for optimization, planning, and decision- making models are studied through a descriptive literature review and a bibliometric analysis of scientific papers published between 1952 and 2016. An upward trend in the usage of operational models is observed with the predominance of resource optimization approaches and strategic decision-making for public health.Los aportes de la Investigación de Operaciones (IO) en el campo de la salud han sido ampliamente estudiados en la literatura científica desde la década de los 60, abarcando el soporte a la decisión en enfoques operacionales, tácticos y estratégicos. Se presenta un resumen del desarrollo histórico de la IO en el campo de la salud y se listan los principales modelos aplicados en los últimos años, identificando el principal enfoque utilizado, y el potencial aporte a la toma de decisiones en el campo de la salud