Skip to main content
padlock icon - secure page this page is secure

Bi-criteria improved genetic algorithm for scheduling in flowshops to minimise makespan and total flowtime of jobs

Buy Article:

$61.00 + tax (Refund Policy)

Bi-criteria improved genetic algorithm (IGA) for flowshop scheduling problem is proposed in this paper. The primary concern of flowshop scheduling problem considered in this work is to obtain the best sequence, which minimises the makespan and total flow time of all jobs. The initial population of the genetic algorithm is created using popular NEH constructive heuristic (Nawaz et al. 1983). In IGA, multi-crossover operators and multi-mutation operators are applied randomly to subpopulations divided from the original population to enhance the exploring potential and to enrich the diversity of the crossover templates. The performance of the proposed algorithm is demonstrated by applying it to benchmark problems available in the OR-Library. Computation results based on some permutation flowshop scheduling benchmark problems (OR-Library) show that the IGA gives better solution when compared with the earlier reported results.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: flowshop scheduling; genetic algorithm; makespan; total flowtime

Document Type: Research Article

Affiliations: 1: Department of Mechanical Engineering, Mepco Schlenk Engineering College, Virudhunagar Dt, Tamil Nadu, India 2: Department of Industrial Engineering, Anna University, Chennai, India

Publication date: October 1, 2009

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more