31 research outputs found

    Analysis and adjustment of a genetic algorithm for non-permutation flowshops

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    The viability of many heuristic procedures strongly depends on the adequate adjustment of parameters. This work presents an adjustment procedure which was applied to a Genetic Algorithm. First, a preliminary analysis is performed, intended to obtain a better understanding of the behavior of the parameters, as for example to estimate how likely it is for the preceding adjustment of the parameters to remain in local minima. Special attention is paid on the variability of the solutions with respect to their repeatability. The four phases of the adjustment procedure are Rough-Adjustment, Repeatability, Clustering and Fine Adjustment

    Extended classification for flowshops with resequencing

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    Este trabajo presenta una clasificación extendida de líneas de flujo no-permutación. Se consideran las múltiples opciones que se presentan al incluir la posibilidad de resecuenciar piezas en la línea. Se ha visto que en la literatura actual no se ha clasificado con profundidad este tipo de producción. Abstract This paper presents an extended cassification for non-permutation flowshops. The versatile options which occur with the possibility of resequencing jobs within the line are considered. The literature review shows that no classification exists which considers extensively this type of flowshop

    A survey of scheduling problems with setup times or costs

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    Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

    Heuristics and metaheuristics for heavily constrained hybrid flowshop problems

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    Due to the current trends in business as the necessity to have a large catalogue of products, orders that increase in frequency but not in size, globalisation and a market that is increasingly competitive, the production sector faces an ever harder economical environment. All this raises the need for production scheduling with maximum efficiency and effectiveness. The first scientific publications on production scheduling appeared more than half a century ago. However, many authors have recognised a gap between the literature and the industrial problems. Most of the research concentrates on optimisation problems that are actually a very simplified version of reality. This allows for the use of sophisticated approaches and guarantees in many cases that optimal solutions are obtained. Yet, the exclusion of real-world restrictions harms the applicability of those methods. What the industry needs are systems for optimised production scheduling that adjust exactly to the conditions in the production plant and that generates good solutions in very little time. This is exactly the objective in this thesis, that is, to treat more realistic scheduling problems and to help closing the gap between the literature and practice. The considered scheduling problem is called the hybrid flowshop problem, which consists in a set of jobs that flow through a number of production stages. At each of the stages, one of the machines that belong to the stage is visited. A series of restriction is considered that include the possibility to skip stages, non-eligible machines, precedence constraints, positive and negative time lags and sequence dependent setup times. In the literature, such a large number of restrictions has not been considered simultaneously before. Briefly, in this thesis a very realistic production scheduling problem is studied. Various optimisation methods are presented for the described scheduling problem. A mixed integer programming model is proposed, in order to obtaiUrlings ., T. (2010). Heuristics and metaheuristics for heavily constrained hybrid flowshop problems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8439Palanci

    Estado del arte del problema de secuenciación de tareas implementando reglas de despacho

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    Este proyecto de investigación es un estado del arte que busca ampliar la información sobre el problema de secuenciación de tareas, teniendo en cuenta las distintas medidas de desempeño y las reglas de despacho usadas actualmente y también a lo largo de las décadas. Con el pasar del tiempo se ve como la tecnología y las teorías frente a la producción evolucionan, cada día se buscan nuevas maneras de optimizar los procesos y mejorar cada una de las áreas que conforman una organización. Este proyecto busca darle una cobertura amplia al problema de secuenciación de tareas usando reglas de despacho, que pueden ser aplicadas mediante distintos métodos como heurísticas y algoritmos, todos ellos encaminados a la optimización de distintos recursos como por ejemplo el tiempo y el costo. La optimización del proceso de producción es una tarea importante que debe resolverse en la planificación estratégica y/u operativa de cada empresa industrial. Todo este concepto lleva a la toma de decisiones, que es vital en cualquier compañía ya que de esta manera se vincula la parte productiva a la gerencial como se evidencia en este proyecto. Las decisiones van ligadas de la mano de distintas áreas para lograr la optimización

    Theoretical and Computational Research in Various Scheduling Models

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    Nine manuscripts were published in this Special Issue on “Theoretical and Computational Research in Various Scheduling Models, 2021” of the MDPI Mathematics journal, covering a wide range of topics connected to the theory and applications of various scheduling models and their extensions/generalizations. These topics include a road network maintenance project, cost reduction of the subcontracted resources, a variant of the relocation problem, a network of activities with generally distributed durations through a Markov chain, idea on how to improve the return loading rate problem by integrating the sub-tour reversal approach with the method of the theory of constraints, an extended solution method for optimizing the bi-objective no-idle permutation flowshop scheduling problem, the burn-in (B/I) procedure, the Pareto-scheduling problem with two competing agents, and three preemptive Pareto-scheduling problems with two competing agents, among others. We hope that the book will be of interest to those working in the area of various scheduling problems and provide a bridge to facilitate the interaction between researchers and practitioners in scheduling questions. Although discrete mathematics is a common method to solve scheduling problems, the further development of this method is limited due to the lack of general principles, which poses a major challenge in this research field
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