Job Shop Scheduling with Alternative Machines Using a Genetic Algorithm Incorporating Heuristic Rules -Effectiveness of Due-Date Related Information- - IFIP-AICT-459
Conference Papers Year : 2015

Job Shop Scheduling with Alternative Machines Using a Genetic Algorithm Incorporating Heuristic Rules -Effectiveness of Due-Date Related Information-

Toru Eguchi
  • Function : Author
  • PersonId : 996259

Abstract

This paper deals with an efficient scheduling method for job shop scheduling with alternative machines with the objective to minimize mean tardiness. The method uses a genetic algorithm incorporating heuristic rules for job sequencing and machine selection. Effective heuristic rules for this method have been proposed so far. However due-date related information has not been included in the heuristic rule for machine selection even though the objective is to minimize mean tardiness. This paper examines the effectiveness of due-date related information for machine selection in this method through numerical experiments.
Fichier principal
Vignette du fichier
346972_1_En_54_Chapter.pdf (145.77 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-01417529 , version 1 (15-12-2016)

Licence

Identifiers

Cite

Parinya Kaweegitbundit, Toru Eguchi. Job Shop Scheduling with Alternative Machines Using a Genetic Algorithm Incorporating Heuristic Rules -Effectiveness of Due-Date Related Information-. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2015, Tokyo, Japan. pp.439-446, ⟨10.1007/978-3-319-22756-6_54⟩. ⟨hal-01417529⟩
189 View
195 Download

Altmetric

Share

More