Busqueda local iterada para resolver problemas de planificación

El diseño de técnicas y algoritmos eficientes que resuelvan adecuadamente problemas complejos de optimización es uno de los campos dentro de la investigación en Informática con mayor repercusión en la actualidad. Por tanto, se han estudiado, diseñado y desarrollado un conjunto heterogéneo de metaheurísticas para resolver importantes problemas de optimización en el campo de la ingeniería. Por tal motivo nuestra propuesta es proporcionar herramientas de software que permitan resolver problemas comunes en la mayoría de las empresas de la región en el sector productivo y en la logística de las mismas.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Busqueda local iterada para resolver problemas de planificación

El diseño de técnicas y algoritmos eficientes que resuelvan adecuadamente problemas complejos de optimización es uno de los campos dentro de la investigación en Informática con mayor repercusión en la actualidad. Por tanto, se han estudiado, diseñado y desarrollado un conjunto heterogéneo de metaheurísticas para resolver importantes problemas de optimización en el campo de la ingeniería. Por tal motivo nuestra propuesta es proporcionar herramientas de software que permitan resolver problemas comunes en la mayoría de las empresas de la región en el sector productivo y en la logística de las mismas.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Busqueda local iterada para resolver problemas de planificación

El diseño de técnicas y algoritmos eficientes que resuelvan adecuadamente problemas complejos de optimización es uno de los campos dentro de la investigación en Informática con mayor repercusión en la actualidad. Por tanto, se han estudiado, diseñado y desarrollado un conjunto heterogéneo de metaheurísticas para resolver importantes problemas de optimización en el campo de la ingeniería. Por tal motivo nuestra propuesta es proporcionar herramientas de software que permitan resolver problemas comunes en la mayoría de las empresas de la región en el sector productivo y en la logística de las mismas.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

A biased-randomized discrete-event algorithm for the hybrid flow shop problem with time dependencies and priority constraints

Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneous jobs are processed by a number of machines. The route that each job has to follow depends upon its type, and, in addition, some machines require that a number of jobs are combined in batches before starting their processing. The hybrid flow model is also subject to a global priority rule and a “same setup” rule. The primary goal of this study was to find a solution set (permutation of jobs) that minimizes the production makespan. While simulation models are frequently employed to model these time-dependent flow shop systems, an optimization component is needed in order to generate high-quality solution sets. In this study, a novel algorithm is proposed to deal with the complexity of the underlying system. Our algorithm combines biased-randomization techniques with a discrete-event heuristic, which allows us to model dependencies caused by batching and different paths of jobs efficiently in a near-natural way. As shown in a series of numerical experiments, the proposed simulation-optimization algorithm can find solutions that significantly outperform those provided by employing state-of-the-art simulation software.Peer ReviewedPostprint (published version

Comparative simulation study of production scheduling in the hybrid and the parallel flow

Scheduling is one of the most important decisions in production control. An approach is proposed for supporting users to solve scheduling problems, by choosing the combination of physical manufacturing system configuration and the material handling system settings. The approach considers two alternative manufacturing scheduling configurations in a two stage product oriented manufacturing system, exploring the hybrid flow shop (HFS) and the parallel flow shop (PFS) environments. For illustrating the application of the proposed approach an industrial case from the automotive components industry is studied. The main aim of this research to compare results of study of production scheduling in the hybrid and the parallel flow, taking into account the makespan minimization criterion. Thus the HFS and the PFS performance is compared and analyzed, mainly in terms of the makespan, as the transportation times vary. The study shows that the performance HFS is clearly better when the work stations' processing times are unbalanced, either in nature or as a consequence of the addition of transport times just to one of the work station processing time but loses advantage, becoming worse than the performance of the PFS configuration when the work stations' processing times are balanced, either in nature or as a consequence of the addition of transport times added on the work stations' processing times. This means that physical layout configurations along with the way transport time are including the work stations' processing times should be carefully taken into consideration due to its influence on the performance reached by both HFS and PFS configurations.This work was supported by National Funds through FCT "Fundacao para a Ciencia e a Tecnologia" under the program: PEst2015-2020, ref. UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Approximation algorithms for the parallel flow shop problem

We consider the NP-hard problem of scheduling n jobs in m two-stage parallel flow shops so as to minimize the makespan. This problem decomposes into two subproblems: assigning the jobs to parallel flow shops; and scheduling the jobs assigned to the same flow shop by use of Johnson's rule. For m = 2, we present a 32-approximation algorithm, and for m = 3, we present a 127-approximation algorithm. Both these algorithms run in O(n log n) time. These are the first approximation algorithms with fixed worst-case performance guarantees for the parallel flow shop problem

A speed-up procedure for the hybrid flow shop scheduling problem

Article number 115903During the last decades, hundreds of approximate algorithms have been proposed in the literature addressing flow-shop-based scheduling problems. In the race for finding the best proposals to solve these problems, speedup procedures to compute objective functions represent a key factor in the efficiency of the algorithms. This is the case of the well-known Taillard’s accelerations proposed for the traditional flow shop with makespan minimisation or several other accelerations proposed for related scheduling problems. Despite the interest in proposing such methods to improve the efficiency of approximate algorithms, to the best of our knowledge, no speed-up procedure has been proposed so far in the hybrid flow shop literature. To tackle this challenge, we propose in this paper a speed-up procedure for makespan minimisation, which can be incorporate in insertion-based neighbourhoods using a complete representation of the solutions. This procedure is embedded in the traditional iterated greedy algorithm. The computational experience shows that even incorporating the proposed speed-up procedure in this simple metaheuristic results in outperforming the best metaheuristic for the problem under consideration.Junta de Andalucía(España) US-1264511Ministerio de Ciencia e Innovación (España) PID2019-108756RB-I0

Modelling and Scheduling Lot Streaming Flexible Flow Lines

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreover, a novel artificial bee colony optimization is developed. This algorithm utilizes five effective mechanisms to solve the problem. To evaluate the algorithm, it is compared with adaptation of four available algorithms. The statistical analyses showed that the proposed algorithm significantly outperformed the other tested algorithms

An Hybrid Genetic Algorithm to Optimization of Flow Shop Scheduling Problems under Real Environments Constraints

This paper aims to analyzing the effect of the inclusion of several constraints that have negative influence in the real manufacturing productions. For the solution of the scheduling problem treated in this paper, known as Flow Shop Scheduling, an efficient Genetic Algorithm is introduced combined with the Variable Neighborhood Search for problems of n tasks and m machines minimizing the total completion time or makespan. Release date, dependent setup-times and transport times are entered. These are common restrictions that can be found in multiple manufacturing environments where there are machines, tools, and a set of jobs must be processed in these, following the same flow pattern. The computational experiments carried out on a set of instances of problems of different sizes of complexity show that the proposed hybrid metaheuristic achieves high quality solutions comparable to the optimum ones reported

Metaheurísticas Basadas en Trayectoria para Resolver una Variante del Problema de Flowshop

El problema de flowshop flexible híbrido con secuencias dependientes del tiempo de puesta a punto es un problema que se puede encontrar en muchos ambientes industriales En este trabajo proponemos algoritmos metaheurísticos basados en trayectoria para resolver dicha variante. Las dos primeras propuestas son algoritmos de enfriamiento simulado que utilizan diferentes operadores de movimiento: intercambio e inserción. La tercera y última propuesta modifica un algoritmo de búsqueda local iterada propuesto en la literatura al reemplazar el operador de inserción por el de intercambio. Los experimentos numéricos comparan el rendimiento de las distintas propuestas, utilizando un amplio conjunto de datos de prueba de uso actual en la literatura. Los resultados muestran que las variantes algorítmicas que aplican el operador de intercambio son más eficientes que las que usan el de inserción para solucionar el problema en estudio.The hybrid flexible flowshop problem with sequence dependent setup times is a problem found in many industrial environments. We propose trajectory-based metaheuristic algorithms to solve this problem. The first two proposals are simulated annealing using different movement operators: insertion and exchange. The third and last proposal modifies an iterated local search algorithm proposed in the literature by changing the insertion operator for the exchange one. Numerical experiments compare the performance of the different proposals using a comprehensive benchmark from the literature. The results show that algorithmic approaches applying the exchange operator are more efficient than the ones using the insertion operator to solve the variant of the flowshop problem.Fil: Minetti, Gabriela Fabiana. Universidad Nacional de la Pampa. Facultad de Ingeniería; ArgentinaFil: Salto, Carolina. Universidad Nacional de la Pampa. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin