Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem

dc.contributor.author Chaurasia, Sachchida Nand
dc.contributor.author Singh, Alok
dc.date.accessioned 2022-03-27T05:54:03Z
dc.date.available 2022-03-27T05:54:03Z
dc.date.issued 2017-03-01
dc.description.abstract This paper presents two hybrid metaheuristic approaches, viz. a hybrid steady-state genetic algorithm (SSGA) and a hybrid evolutionary algorithm with guided mutation (EA/G) for order acceptance and scheduling (OAS) problem in a single machine environment where orders are supposed to have release dates and sequence dependent setup times are incurred in switching from one order to next in the schedule. OAS problem is an NP-hard problem. We have compared our approaches with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approaches.
dc.identifier.citation Applied Soft Computing Journal. v.52
dc.identifier.issn 15684946
dc.identifier.uri 10.1016/j.asoc.2016.09.051
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S1568494616305105
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8682
dc.subject Estimation of distribution algorithm
dc.subject Evolutionary algorithm
dc.subject Guided mutation
dc.subject Order acceptance and scheduling
dc.subject Sequence dependent setup time
dc.subject Single machine scheduling
dc.subject Steady-state genetic algorithm
dc.title Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem
dc.type Journal. Article
dspace.entity.type
Files
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: