Skip to main content
Springer Nature Link
Log in

A Genetic Algorithm for the Economic Lot Scheduling Problem under Extended Basic Period Approach and Power-of-Two Policy

  • 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:

  • 3539 Accesses

Abstract

In this study, we propose a genetic algorithm (GA) for the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. The proposed GA employs a multi-chromosome solution representation to encode PoT multipliers and the production positions separately. Both feasible and infeasible solutions are maintained in the population through the use of some sophisticated constraint handling methods. Furthermore, a variable neighborhood search (VNS) algorithm is also fused into GA to further enhance the solution quality. The experimental results show that the proposed GA is very competitive to the best performing algorithms from the existing literature under the EBP and PoT policy.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Hanssmann, F.: Operation Research in Production and Inventory. Wiley, New York (1962)

    MATH  Google Scholar 

  2. Bomberger, E.E.: A dynamic programming approach to a lot size scheduling problem. Management Science 12, 778–784 (1966)

    Article  MATH  Google Scholar 

  3. Elmaghraby, S.E.: The Economic Lot Scheduling Problem (ELSP): Review and Extensions. Management Science 24, 587–598 (1978)

    Article  MATH  Google Scholar 

  4. Sun, H., Huang, H., Jaruphongsa, W.: The Economic Lot Scheduling Problem under Extended Basic Period and Power-of-two Policy. Optimization Letters 4, 157–172 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chatfield, D.: The Economic Lot Scheduling Problem: a Pure Genetic Search Approach. Computers and Operations Research 34, 2865–2881 (1987)

    Article  MATH  Google Scholar 

  6. Sun, H., Huang, H.C., Jaruphongsa, W.: A Genetic Algorithm for the Economic Lot Scheduling Problem under the Extended Basic Period and Power-of-two Policy. CIRP Journal of Manufacturing Science and Technology 2, 29–34 (2009)

    Article  Google Scholar 

  7. Gen, M., Cheng, R.: Genetic Algorithms and Engineering Design. Wiley Series in Engineering Design and Automation. John Wiley & Sons, Chichester (1997)

    Google Scholar 

  8. Coello, A.C.: Theoretical and Numerical Constraint-Handling Techniques Used with Evolutionary Algorithms: A Survey of the State of the Art. Comput. Methods Appl. Mech. Engrg. 191(11-12), 1245–1287 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  9. Deb, K.: An Efficient Constraint Handling Method for Genetic Algorithms. Computer Methods in Applied Mechanics and Engineering 186, 311–338 (2000)

    Article  MATH  Google Scholar 

  10. Takahama, T., Sakai, S.: Tuning Fuzzy Control Rules by the α Constrained Dethod Which Solves Constrained Nonlinear Optimization Problems. Electronics and Communications in Japan, Part3: Fundamental Electronic Science 83(9), 1–12 (2000)

    Article  Google Scholar 

  11. Mladenovic, N., Hansen, P.: Variable Neighborhood Search. Computers and Operations Research 24, 1097–1100 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  12. Haessler, R.: An Improved Extended Basic Period Procedure for Solving the Economic Lot Scheduling Problem. AIIE Transactions 11, 336–340 (1979)

    Article  Google Scholar 

  13. Khouja, M., Michalewicz, Z., Wilmot, M.: The Use of Genetic Algorithms to Solve the Economic Lot Size Scheduling Problem. European Journal of Operational Research 110, 509–524 (1998)

    Article  MATH  Google Scholar 

  14. Park, K.S., Yun, D.K.: A Stepwise Partial Enumeration Algorithm for the Economic Lot Scheduling Problem. IIE Transactions 16, 363–370 (1984)

    Article  Google Scholar 

  15. Fujita, S.: The Application of Marginal Analysis to the ELSP. AIIE Transactions 10(4), 354–361 (1978)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Yasar University, Izmir, Turkey

    Onder Bulut & M. Fatih Tasgetiren

  2. Industrial and Systems Engineering Department, Izmir Economy University, Izmir, Turkey

    M. Murat Fadiloglu

Authors
  1. Onder Bulut
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Fatih Tasgetiren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Murat Fadiloglu
    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

Bulut, O., Tasgetiren, M.F., Fadiloglu, M.M. (2012). A Genetic Algorithm for the Economic Lot Scheduling Problem under Extended Basic Period Approach and Power-of-Two Policy. 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_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25944-9_8

  • 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