Skip to main content
SpringerLink
Log in

A Multi-objective Hybrid Discrete Harmony Search Algorithm for Lot-Streaming Flow Shop Scheduling Problem

  • Conference paper
Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

Included in the following conference series:

  • 3431 Accesses

Abstract

In this paper, a multi-objective discrete harmony search algorithm (MDHS) is proposed to slove the lot-streaming flow shop scheduling problem with respect to the two objectives of makespan and total flow time. In the MDHS algorithm, the harmonies are represented as discrete job permutations, and an efficient initialization scheme, which is based on the famous NEH heuristic, is presented to construct the an initial solution in harmony memory. In addition, a local search approach based on insertion operator is embedded to improve the efficiency of the MDHS algorithm. Through the analysis of computational results, the proposed algorithm is superior to NEH heuristic algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Yoon, S.H., Ventura, J.A.: An Application of Genetic Algorithms to Lot-straming Flow Shop Scheduling. IIE Transactions 34, 779–787 (2002)

    Google Scholar 

  2. Pan, Q.K., Pn, S.T., Tasgetiren, M.F., Chua, T.J.: A Novel Artificial Bee Colony Algorithm for a Lot-streaming Flow Shop Scheduling Problem. Information Sciences 181, 2455–2468 (2011)

    Article  MathSciNet  Google Scholar 

  3. Marimuthu, S., Ponnambalam, S.G., Jawahar, N.: Threshold Accepting and Ant-colony Optimization Algorithms for Scheduling M-machine Flow Shops with Lot Streaming. Journal of Materials Processing Technology 209, 1026–1041 (2009)

    Article  Google Scholar 

  4. Tseng, C.T., Liao, C.J.: A Discrete Particle Swarm Optimization for Lot-streaming Flow Shop Scheduling Problem. European Journal of Operation Research 191, 360–373 (2008)

    Article  MATH  Google Scholar 

  5. Pan, Q.K., Tasgetiren, M.F., Liang, Y.C.: A Discrete Particle Swarm Optimization Algorithm for the No-wait Flowshop Scheduling Problem. Computers and Operations Research 35, 2807–2839 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  6. Varadharajan, T.K., Rajendran, C.: A Multi-objective Simulated-annealing Algorithm for Scheduling in Flowshops to Minimize the Makespan and Total Flowtime of Jobs. European Journal of Operational Research 167, 722–795 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  7. Pan, Q.K., Wang, L., Qian, B.: A Novel Differential Evolution Algorithm for Bi-criteria No-wait Flow Shop Scheduling Problems. Computers & Operations Research 36, 2498–2511 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  8. Tavakkoli, M.R., Rahimi, V.A., Mirzaei, A.H.: A Hybrid Multi-objective Immune Algorithm for a Flow Shop Scheduling Problem with Bi-objectives: Weighted Mean Completion Time and Weighted Mean Tardiness. Information Sciences 177, 5072–5090 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  9. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A New Heuristic Optimization Algorithm: Harmony Search. Simulation 76, 60–68 (2001)

    Article  Google Scholar 

  10. Mahamed, G.H., Omran, M.M.: Global-best Harmony Search. Applied Mathematics and Computation 198, 643–656 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  11. Pan, Q.K., Suganthan, P.N., Tasgetiren, M.F.: A Self-Adaptive Global Best Harmony Search Algorithm for Continuous Optimization Problems. Applied Mathematics and Computation 206, 830–848 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kalczynski, P.J., Kamburowski, J.: On the NEH Heuristic for Minimizing the Makespan in Permutation Flowshops. The International Journal of Management Sciences 35, 53–60 (2007)

    Google Scholar 

  13. Pan, Q., Duan, J.H., Liang, J.J., Gao, K.Z., Li, J.Q.: A Novel Discrete Harmony Search Algorithm for Scheduling Lot-streaming Flow Shops. In: Proceeding of the 22nd Chinese Control and Decision Conference (CCDC 2010), Xuzhou, China, pp. 1531–1536 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Mathematics Science, Liaocheng University, Liaocheng, 252059, China

    Hong-Yan Han

Authors
  1. Hong-Yan Han
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Han, HY. (2012). A Multi-objective Hybrid Discrete Harmony Search Algorithm for Lot-Streaming Flow Shop Scheduling Problem. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25944-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation