595 research outputs found
ILS-ESP: An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem
From a managerial point of view, the more e cient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be
used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop
Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP
algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most
e cient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can a ect their
performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic ‘common
sense’ rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new
operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased
randomization process of the initial solution to randomly generate di erent alternative initial solutions of similar quality -which is
attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding
poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed
computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and
compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art
metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top
ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number
generator.Preprin
Internet of Things in urban waste collection
Nowadays, the waste collection management has an important role in urban areas. This paper faces this issue and proposes the application of a metaheuristic for the optimization of a weekly schedule and routing of the waste collection activities in an urban area. Differently to several contributions in literature, fixed periodic routes are not imposed. The results significantly improve the performance of the company involved, both in terms of resources used and costs saving
Stochastic local search: a state-of-the-art review
The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stochastic local search techniques used for solving hard combinatorial problems. It begins with a short introduction, motivation and some basic notation on combinatorial problems, search paradigms and other relevant features of searching techniques as needed for background. In the following a brief overview of the stochastic local search methods along with an analysis of the state-of-the-art stochastic local search algorithms is given. Finally, the last part of the paper present and discuss some of the most latest trends in application of stochastic local search algorithms in machine learning, data mining and some other areas of science and engineering. We conclude with a discussion on capabilities and limitations of stochastic local search algorithms
N-list-enhanced heuristic for distributed three-stage assembly permutation flow shop scheduling
System-wide optimization of distributed manufacturing operations enables process improvement beyond the standalone and individual optimality norms. This study addresses the production planning of a distributed manufacturing system consisting of three stages: production of parts (subcomponents), assembly of components in Original Equipment Manufacturer (OEM) factories, and final assembly of products at the product manufacturer’s factory. Distributed Three Stage Assembly Permutation Flowshop Scheduling Problems (DTrSAPFSP) models this operational situation; it is the most recent development in the literature of distributed scheduling problems, which has seen very limited development for possible industrial applications. This research introduces a highly efficient constructive heuristic to contribute to the literature on DTrSAPFSP. Numerical experiments considering a comprehensive set of operational parameters are undertaken to evaluate the performance of the benchmark algorithms. It is shown that the N-list-enhanced Constructive Heuristic algorithm performs significantly better than the current best-performing algorithm and three new metaheuristics in terms of both solution quality and computational time. It can, therefore, be considered a competitive benchmark for future studies on distributed production scheduling and computing
A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation
[EN] The permutation flowshop problem is a classic machine scheduling problem where n jobs must be processed on a set of m machines disposed in series and where each job must visit all machines in the same order. Many production scheduling problems resemble flowshops and hence it has generated much interest and had a big impact in the field, resulting in literally hundreds of heuristic and metaheuristic methods over the last 60 years. However, most methods proposed for makespan minimisation are not properly compared with existing procedures so currently it is not possible to know which are the most efficient methods for the problem regarding the quality of the solutions obtained and the computational effort required. In this paper, we identify and exhaustively compare the best existing heuristics and metaheuristics so the state-of-the-art regarding approximate procedures for this relevant problem is established. (C) 2016 Elsevier B.V. All rights reserved.The authors are sincerely grateful to the anonymous referees, who provide very valuable comments on the earlier version of the paper. This research has been funded by the Spanish Ministry of Science and Innovation, under projects "ADDRESS" (DPI2013-44461-P/DPI) and "SCHEYARD" (DPI2015-65895-R) co-financed by FEDER funds.Fernandez-Viagas, V.; Ruiz GarcÃa, R.; Framinan, J. (2017). A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation. European Journal of Operational Research. 257(3):707-721. https://doi.org/10.1016/j.ejor.2016.09.055S707721257
Comparative Analysis of Metaheuristic Approaches for Makespan Minimization for No Wait Flow Shop Scheduling Problem
This paper provides comparative analysis of various metaheuristic approaches for m-machine no wait flow shop scheduling (NWFSS) problem with makespan as an optimality criterion. NWFSS problem is NP hard and brute force method unable to find the solutions so approximate solutions are found with metaheuristic algorithms. The objective is to find out the scheduling sequence of jobs to minimize total completion time. In order to meet the objective criterion, existing metaheuristic techniques viz. Tabu Search (TS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are implemented for small and large sized problems and effectiveness of these techniques are measured with statistical metric
The Distributed and Assembly Scheduling Problem
Tesis por compendio[EN] Nowadays, manufacturing systems meet different new global challenges and
the existence of a collaborative manufacturing environment is essential to face
with. Distributed manufacturing and assembly systems are two manufacturing
systems which allow industries to deal with some of these challenges. This
thesis studies a production problem in which both distributed manufacturing
and assembly systems are considered. Although distributed manufacturing
systems and assembly systems are well-known problems and have been extensively
studied in the literature, to the best of our knowledge, considering
these two systems together as in this thesis is the first effort in the literature.
Due to the importance of scheduling optimization on production performance,
some different ways to optimize the scheduling of the considered problem are
discussed in this thesis.
The studied scheduling setting consists of two stages: A production and an
assembly stage. Various production centers make the first stage. Each of these
centers consists of several machines which are dedicated to manufacture jobs.
A single assembly machine is considered for the second stage. The produced
jobs are assembled on the assembly machine to form final products through a
defined assembly program.
In this thesis, two different problems regarding two different production
configurations for the production centers of the first stage are considered.
The first configuration is a flowshop that results in what we refer to as the
Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP).
The second problem is referred to as the Distributed Parallel Machine and
Assembly Scheduling Problem (DPMASP), where unrelated parallel machines
configure the production centers. Makespan minimization of the product on the
assembly machine located in the assembly stage is considered as the objective
function for all considered problems.
In this thesis some extensions are considered for the studied problems
so as to bring them as close as possible to the reality of production shops.
In the DAPFSP, sequence dependent setup times are added for machines in
both production and assembly stages. Similarly, in the DPMASP, due to
technological constraints, some defined jobs can be processed only in certain
factories.
Mathematical models are presented as an exact solution for some of the
presented problems and two state-of-art solvers, CPLEX and GUROBI are
used to solve them. Since these solvers are not able to solve large sized
problems, we design and develop heuristic methods to solve the problems. In
addition to heuristics, some metaheuristics are also designed and proposed to
improve the solutions obtained by heuristics. Finally, for each proposed problem,
the performance of the proposed solution methods is compared through
extensive computational and comprehensive ANOVA statistical analysis.[ES] Los sistemas de producción se enfrentan a retos globales en los que el concepto
de fabricación colaborativa es crucial para poder tener éxito en el entorno
cambiante y complejo en el que nos encontramos. Una caracterÃstica de los sistemas
productivos que puede ayudar a lograr este objetivo consiste en disponer
de una red de fabricación distribuida en la que los productos se fabriquen en
localizaciones diferentes y se vayan ensamblando para obtener el producto
final. En estos casos, disponer de modelos y herramientas para mejorar el
rendimiento de sistemas de producción distribuidos con ensamblajes es una
manera de asegurar la eficiencia de los mismos.
En esta tesis doctoral se estudian los sistemas de fabricación distribuidos
con operaciones de ensamblaje. Los sistemas distribuidos y los sistemas con
operaciones de ensamblaje han sido estudiados por separado en la literatura.
De hecho, no se han encontrado estudios de sistemas con ambas caracterÃsticas
consideradas de forma conjunta.
Dada la complejidad de considerar conjuntamente ambos tipos de sistemas
a la hora de realizar la programación de la producción en los mismos, se ha
abordado su estudio considerando un modelo bietápico en la que en la primera
etapa se consideran las operaciones de producción y en la segunda se plantean
las operaciones de ensamblaje.
Dependiendo de la configuración de la primera etapa se han estudiado dos
variantes. En la primera variante se asume que la etapa de producción está
compuesta por sendos sistemas tipo flowshop en los que se fabrican los componentes
que se ensamblan en la segunda etapa (Distributed Assembly Permutation
Flowshop Scheduling Problem o DAPFSP). En la segunda variante
se considera un sistema de máquinas en paralelo no relacionadas (Distributed
Parallel Machine and Assembly Scheduling Problem o DPMASP). En ambas
variantes se optimiza la fecha de finalización del último trabajo secuenciado
(Cmax) y se contempla la posibilidad que existan tiempos de cambio (setup)
dependientes de la secuencia de trabajos fabricada. También, en el caso
DPMASP se estudia la posibilidad de prohibir o no el uso de determinadas
máquinas de la etapa de producción.
Se han desarrollado modelos matemáticos para resolver algunas de las
variantes anteriores. Estos modelos se han resuelto mediante los programas
CPLEX y GUROBI en aquellos casos que ha sido posible. Para las instancias
en los que el modelo matemático no ofrecÃa una solución al problema se han
desarrollado heurÃsticas y metaheurÃsticas para ello.
Todos los procedimientos anteriores han sido estudiados para determinar
el rendimiento de los diferentes algoritmos planteados. Para ello se ha realizado
un exhaustivo estudio computacional en el que se han aplicado técnicas
ANOVA.
Los resultados obtenidos en la tesis permiten avanzar en la comprensión
del comportamiento de los sistemas productivos distribuidos con ensamblajes,
definiendo algoritmos que permiten obtener buenas soluciones a este tipo de
problemas tan complejos que aparecen tantas veces en la realidad industrial.[CA] Els sistemes de producció s'enfronten a reptes globals en què el concepte de
fabricació col.laborativa és crucial per a poder tindre èxit en l'entorn canviant
i complex en què ens trobem. Una caracterÃstica dels sistemes productius
que pot ajudar a aconseguir este objectiu consistix a disposar d'una xarxa de
fabricació distribuïda en la que els productes es fabriquen en localitzacions
diferents i es vagen acoblant per a obtindre el producte final. En estos casos,
disposar de models i ferramentes per a millorar el rendiment de sistemes de
producció distribuïts amb acoblaments és una manera d'assegurar l'eficiència
dels mateixos.
En esta tesi doctoral s'estudien els sistemes de fabricació distribuïts amb
operacions d'acoblament. Els sistemes distribuïts i els sistemes amb operacions
d'acoblament han sigut estudiats per separat en la literatura però, en allò
que es coneix, no s'han trobat estudis de sistemes amb ambdós caracterÃstiques
conjuntament. Donada la complexitat de considerar conjuntament ambdós
tipus de sistemes a l'hora de realitzar la programació de la producció en els
mateixos, s'ha abordat el seu estudi considerant un model bietà pic en la que
en la primera etapa es consideren les operacions de producció i en la segona es
plantegen les operacions d'acoblament.
Depenent de la configuració de la primera etapa s'han estudiat dos variants.
En la primera variant s'assumix que l'etapa de producció està composta per
sengles sistemes tipus flowshop en els que es fabriquen els components que
s'acoblen en la segona etapa (Distributed Assembly Permutation Flowshop
Scheduling Problem o DAPFSP). En la segona variant es considera un sistema
de mà quines en paral.lel no relacionades (Distributed Parallel Machine and
Assembly Scheduling Problem o DPMASP). En ambdós variants s'optimitza
la data de finalització de l'últim treball seqüenciat (Cmax) i es contempla la
possibilitat que existisquen temps de canvi (setup) dependents de la seqüència
de treballs fabricada. També, en el cas DPMASP s'estudia la possibilitat de
prohibir o no l'ús de determinades mà quines de l'etapa de producció.
S'han desenvolupat models matemà tics per a resoldre algunes de les variants
anteriors. Estos models s'han resolt per mitjà dels programes CPLEX
i GUROBI en aquells casos que ha sigut possible. Per a les instà ncies en
què el model matemà tic no oferia una solució al problema s'han desenrotllat
heurÃstiques i metaheurÃsticas per a això. Tots els procediments anteriors han
sigut estudiats per a determinar el rendiment dels diferents algoritmes plantejats.
Per a això s'ha realitzat un exhaustiu estudi computacional en què s'han
aplicat tècniques ANOVA.
Els resultats obtinguts en la tesi permeten avançar en la comprensió del
comportament dels sistemes productius distribuïts amb acoblaments, definint
algoritmes que permeten obtindre bones solucions a este tipus de problemes
tan complexos que apareixen tantes vegades en la realitat industrial.Hatami, S. (2016). The Distributed and Assembly Scheduling Problem [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64072TESISCompendi
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