Modelling of heuristic distribution algorithm to optimize flexible production scheduling in Indian industry

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1120-1127
Journal / PublicationProcedia Computer Science
Volume167
Online published16 Apr 2020
Publication statusPublished - 2020

Conference

Title2019 International Conference on Computational Intelligence and Data Science, ICCIDS 2019
PlaceIndia
CityGurugram
Period6 - 7 September 2019

Link(s)

Abstract

Multi-objective scheduling with the NP-dependent relay preparation time becomes difficult because the complexity of the optimization increases within a reasonable time. Research methods have become a more important option to solve the difficult problems of NP because there are more powerful solutions and a great potential to require biology in a reasonable time. In the present work, Two Heuristic Algorithms are modelled and the best algorithm among those two Heuristics is selected after few comparisons 3M to 5M, this can optimize the scheduling processes up to 10x10 jobs i.e. 10 machines and 10 jobs. In context of Heuristic optimization, the results clearly show the variation in times (decrease) of all-time dependents i.e. 46% decrease, when the increase in machines and jobs are considered, therefore, it implicates the error of 0.468 as the make-span decreased by 221 minutes. The proposed model gives a large edge in minimization of make-span i.e., 40-50% decrease in the production times, and it can produce even more when the number of sources and jobs are more. Therefore, the optimized error of 0.456 than the mathematical data and hence, this model is validated.

Research Area(s)

  • ant colony optimization, bound, branch, genetic algorithm, heuristics, Scheduling

Citation Format(s)

Modelling of heuristic distribution algorithm to optimize flexible production scheduling in Indian industry. / Reddy, Guduru Ramakrishna; Singh, Harpreet; Domeika, Aurelijus; Kumar, Nallapaneni Manoj; Quanjin, Ma.

In: Procedia Computer Science, Vol. 167, 2020, p. 1120-1127.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

Download Statistics

No data available