Authors: Yuerong Chen, Xueping Li, Rapinder Sawhney
Addresses: Department of Industrial and Information Engineering, University of Tennessee, Knoxville, TN 37996-0700, USA. ' Department of Industrial and Information Engineering, University of Tennessee, 408 East Stadium Hall, Knoxville, TN 37996-0700, USA. ' Department of Industrial and Information Engineering, University of Tennessee, Knoxville, TN 37996-0700, USA
Abstract: This paper is concerned with scheduling a number of jobs on multiple identical parallel machines to minimise job Completion Time Variance (CTV), which is a performance measure that emphasises providing uniform service to jobs. CTV minimisation is closely related to common due date problems, service stability and the Just-in-Time (JIT) philosophy. This paper focuses on the restricted aspect of the problem, i.e., no idle times are allowed to insert before machines start to process jobs. By exploring the properties of optimal schedules, we develop a computationally efficient heuristic algorithm named Balanced Assignment, Verified Schedule (BAVS) to reduce job CTV. This paper takes into account the deterministic case in which the processing times of jobs are known in advance. Numerical results show that the BAVS algorithm is near-optimal for small-sized problem instances and outperforms some existing algorithms for large-sized problem instances. [Submitted 01 February 2008; Revised 02 July 2008; Accepted 21 October 2008]
Keywords: job scheduling; completion time variance; CTV; service stability; production planning; identical machines; parallel machines; parallel machine scheduling.
European Journal of Industrial Engineering, 2009 Vol.3 No.3, pp.261 - 276
Published online: 10 May 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article