SciELO - Scientific Electronic Library Online

 
vol.38 issue3Paraná's Credit Unions: an analysis of their efficiency and productivity change author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Ingeniería e Investigación

Print version ISSN 0120-5609

Abstract

CHAUDHRY, Imran Ali; ELBADAWI, Isam A-Q.; USMAN, Muhammad  and  TAJAMMAL CHUGTAI, Muhammad. Minimising Total Flowtime in a No-Wait Flow Shop (NWFS) using Genetic Algorithms. Ing. Investig. [online]. 2018, vol.38, n.3, pp.68-79. ISSN 0120-5609.  http://dx.doi.org/10.15446/ing.investig.v38n3.75281.

This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented in a spreadsheet environment. The GA functions as an add-in in the spreadsheet. It is demonstrated that with proposed approach any criteria can be optimised without modifying the GA routine or spreadsheet model. Furthermore, the proposed method for solving this class of problem is general purpose, as it can be easily customised by adding or removing jobs and machines. Several benchmark problems already published in the literature are used to demonstrate the problem-solving capability of the proposed approach. Benchmark problems set ranges from small (7-jobs, 7 machines) to large (100-jobs, 10-machines). The performance of the GA is compared with different meta-heuristic techniques used in earlier literature. Experimental analysis demonstrate that solutions obtained in this research offer equal quality as compared to algorithms already developed for NWFS problems.

Keywords : Genetic algorithm (GA); Scheduling; No-wait; Flow shop.

        · abstract in Spanish     · text in English     · English ( pdf )