• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2018.tde-11122017-123449
Document
Author
Full name
Julio Cesar Delgado Vasquez
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2017
Supervisor
Committee
Birgin, Ernesto Julian Goldberg (President)
Mesquita, Marco Aurélio de
Oliveira, Alexandre César Muniz de
Title in Portuguese
Programação de tarefas em um ambiente flow shop com m máquinas para a minimização do desvio absoluto total de uma data de entrega comum
Keywords in Portuguese
Adiantamento
Algoritmo de timing
Atraso
Data de entrega comum
Flow shop
Heurística
Permutação
Abstract in Portuguese
Neste trabalho abordamos o problema de programação de tarefas em um ambiente flow shop permutacional com mais de duas máquinas. Restringimos o estudo para o caso em que todas as tarefas têm uma data de entrega comum e restritiva, e onde o objetivo é minimizar a soma total dos adiantamentos e atrasos das tarefas em relação a tal data de entrega. É assumido também um ambiente estático e determinístico. Havendo soluções com o mesmo custo, preferimos aquelas que envolvem menos tempo de espera no buffer entre cada máquina. Devido à dificuldade de resolver o problema, mesmo para instâncias pequenas (o problema pertence à classe NP-difícil), apresentamos uma abordagem heurística para lidar com ele, a qual está baseada em busca local e faz uso de um algoritmo linear para atribuir datas de conclusão às tarefas na última máquina. Este algoritmo baseia-se em algumas propriedades analíticas inerentes às soluções ótimas. Além disso, foi desenvolvida uma formulação matemática do problema em programação linear inteira mista (PLIM) que vai permitir validar a eficácia da abordagem. Examinamos também o desempenho das heurísticas com testes padrões (benchmarks) e comparamos nossos resultados com outros obtidos na literatura.
Title in English
Scheduling in a n-machine flow shop for the minimization of the total absolute deviation from a common due date
Keywords in English
Common due date
Earliness
Flow shop
Heuristic
Permutation
Tardiness
Timing algorithm
Abstract in English
In this work we approach the permutational flow shop scheduling problem with more than two machines. We restrict the study to the case where all the jobs have a common and restrictive due date, and where the objective is to minimize the total sum of the earliness and tardiness of jobs relative to the due date. A static and deterministic environment is also assumed. If there are solutions with the same cost, we prefer those that involve less buffer time between each machine. Due to the difficulty of solving the problem, even for small instances (the problem belongs to the NP-hard class), we present a heuristic approach to dealing with it, which is based on local search and makes use of a linear algorithm to assign conclusion times to the jobs on the last machine. This algorithm is based on some analytical properties inherent to optimal solutions. In addition, a mathematical formulation of the problem in mixed integer linear programming (MILP) was developed that will validate the effectiveness of the approach. We also examined the performance of our heuristics with benchmarks and compared our results with those obtained in the literature.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
texto_julio_delgado.pdf (568.59 Kbytes)
Publishing Date
2018-04-16
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
CeTI-SC/STI
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2024. All rights reserved.