Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Some Investigations on Drilling of Aluminium Alloy from FEA-Based Simulation Using DEFORM-3D Read chapter Read first chapter

2020 | OriginalPaper | Chapter

21. Development and Analysis of a Discrete Particle Swarm Optimisation for Bi-criteria Scheduling of a Flow Shop with Sequence-Dependent Setup Time

Authors : V. Anjana, R. Sridharan, P. N. Ram Kumar

Published in: Advances in Simulation, Product Design and Development

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Most studies in flow shop scheduling neglect the setup times or consider the setup times along with the processing times. However, in industries that manufacture paint, textiles, ceramic tiles, etc., the setup times are significant and are sequence dependent. This paper addresses the problem of scheduling a flow shop operating in a sequence-dependent setup time (SDST) environment considering the objectives, namely minimisation of makespan and mean tardiness. The evolutionary method of discrete particle swarm optimisation (DPSO) based on weighted approach is developed and applied to SDST benchmark problems of flow shop scheduling. The efficacy of the metaheuristic is compared with that of a hybrid genetic algorithm, and it is observed that on an average, the proposed DPSO provides an improvement of 7.8, 22.3 and 11.3% in the values of mean ideal distance, computational time and diversification matrix, respectively. For most problems, the proposed DPSO performs superior to the hybrid genetic algorithm.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter FEA of Electrical Discharge Machining on the Particle Metal Matrix Composite
next chapter A MATLAB-Based Application to Solve Vehicle Routing Problem Using GA
Literature
1.
Ruiz, R., Maroto, C., Alcaraz, J.: Solving the flow shop scheduling problem with sequence dependent setup times using advanced metaheuristic. Eur. J. Oper. Res. 165(1), 34–54 (2005)CrossRef
2.
Ciavotta, M., Minella, G., Ruiz, R.: Multi-objective sequence dependent setup times permutation flow shop: a new algorithm and comprehensive study. Eur. J. Oper. Res. 227(2), 301–313 (2013)CrossRef
3.
Vanchipura, R., Sridharan, R.: Development and analysis of constructive heuristic algorithms for flow shop scheduling problems with sequence dependent setup times. Int. J. Adv. Manuf. Technol. 67(5), 1337–1353 (2013)CrossRef
4.
Roger, Z., Mercado, R., Bard, J.: Computational experience with a branch and cut algorithm for flow shop scheduling with setups. Comput. Oper. Res. 25(5), 351–366 (1998)CrossRef
5.
Roger, Z., Mercado, R., Bard, J.: A branch and bound algorithm for permutation flow shops with sequence dependent setup times. IIE Trans. 31, 721–731 (1999)
6.
Deb, K.: Multi-objective Optimisation Using Evolutionary Algorithms, Student ed. Wiley, Hoboken (2005)
7.
Rajendran, C., Ziegler, H.: Scheduling to minimise the sum of weighted flow time and weighted tardiness of jobs in a flow shop with sequence dependent setup time. Eur. J. Oper. Res. 149(3), 513–522 (2003)CrossRef
8.
Eren, T., Guner, E.: A bi-criteria scheduling with sequence dependent setup time. Appl. Math. Comput. 179(1), 378–385 (2006)MathSciNetMATH
9.
Eren, T.: A multi-criteria flow shop scheduling problem with setup times. J. Mater. Process. Technol. 186(1–3), 60–65 (2007)CrossRef
10.
Dhingra, A., Chandna, P.: A bi-criteria m-machine sequence dependent setup time flow shop using modified heuristic genetic algorithm. Int. J. Eng. Sci. Technol. 2(5), 216–225 (2010)CrossRef
11.
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948. Piscataway, NJ (1995)
12.
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. IEEE 4104–4108
13.
Pan, Q., Tasgetiren, F., Liang, Y.C.: A discrete particle swarm optimisation algorithm for no-wait flow shop scheduling problem. Eur. J. Oper. Res. 35(9), 2807–2839 (2008)MATH
14.
Enscore Jr., E., Ham, I., Nawaz, M.: A heuristic algorithm for the m-machine, n-job flow shop sequencing problem. Omega Int. J. Manage. Sci. 11(1), 91–97 (1983)CrossRef
15.
Ross, P.J.: Taguchi Techniques for Quality Engineering, 2nd ed. McGraw Hill International Editions (1996)
16.
Kaladhar, M., Subbaiah, K.V., Rao, S., Rao, K.N.: Application of Taguchi approach and utility concept in solving the multi-objective problem when turning AISI 202 Austenitic Stainless Steel. J. Eng. Sci. Technol. Rev. 4(1), 55–61 (2011)CrossRef
17.
Metadata
Title
Development and Analysis of a Discrete Particle Swarm Optimisation for Bi-criteria Scheduling of a Flow Shop with Sequence-Dependent Setup Time
Authors
V. Anjana
R. Sridharan
P. N. Ram Kumar
Copyright Year
2020
Publisher
Springer Singapore
Book
Advances in Simulation, Product Design and Development

Print ISBN: 978-981-329-486-8

Electronic ISBN: 978-981-329-487-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-32-9487-5_21

Premium Partners

    Image Credits