Skip to main content
SpringerLink
Log in

Solving 0/1 Knapsack Problem Using Hybrid TLBO-GA Algorithm

  • Conference paper
  • First Online:
Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 335))

Abstract

The 0/1 knapsack problem is attempted to solve using various soft computing methods till date. This paper proposes hybrid TLBO-GA algorithm which is hybrid of teaching learning-based optimization (TLBO) algorithm with genetic algorithm (GA). The 0/1 knapsack problem is a combinatorial optimization problem. The 0/1 knapsack problem aims to maximize the benefit of objects in a knapsack without exceeding its capacity as a constraint. In the literature, it is found that TLBO works for real-coded or real-valued problems. Hybrid TLBO-GA combines evolutionary process of TLBO and binary chromosome representation of GA for solving the knapsack problem (KP). Hybrid TLBO-GA combines advantages of both TLBO and GA. Results are taken on random as well as standard date sets using hybrid TLBO-GA for 0/1 knapsack problem. Hybrid TLBO-GA results are compared with the results obtained using simple genetic algorithm (SGA) on the same data sets. The results obtained using hybrid TLBO-GA are found satisfactory.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

References

  1. Hristakeva, M., Shrestha, D: Solving the 0-1 knapsack problem with genetic Algorithms. In: Proceedings of the 37th Midwest Instruction and Computing Symposium, Morris, MN (2004)

    Google Scholar 

  2. Rao, R., Savsani, V., Vakharia, D.: Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43(3), 303–315 (2011)

    Article  Google Scholar 

  3. Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching–learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf. Sci. 183(1), 1–15 (2012)

    Article  MathSciNet  Google Scholar 

  4. KNAPSACK_01—Data for the 01 knapsack problem. http://people.sc.fsu.edu/~jburkardt/datasets/knapsack_01/p07_c.txt. 8 Sept 2014

  5. https://github.com/jkdeveyra/CMSC-170-KnapsackGA/tree/master/src/main/java/dataset. 12 Aug 2013

  6. Umbarkar, A., Joshi, M.: 0/1 knapsack problem using diversity based dual population genetic algorithm. Int. J. Intell. Syst. Appl. (IJISA) 6(10), 34–40 (2014). doi:10.5815/ijisa.2014.10.05

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Walchand College of Engineering, Sangli, Maharashtra, India

    A. J. Umbarkar, P. D. Sheth & S. V. Babar

Authors
  1. A. J. Umbarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. D. Sheth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. V. Babar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. J. Umbarkar .

Editor information

Editors and Affiliations

  1. Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  3. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  4. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  5. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Umbarkar, A.J., Sheth, P.D., Babar, S.V. (2015). Solving 0/1 Knapsack Problem Using Hybrid TLBO-GA Algorithm. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2217-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2217-0_1

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2216-3

  • Online ISBN: 978-81-322-2217-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation