Completion time variance minimization in single machine and multi-machine systems

In this paper we consider the problem of minimizing the completion time variance of n jobs on a single machine with deterministic processing times. We propose a new heuristic and compare the results with existing popular heuristics for the problem. We also propose a method based on genetic algorithm...

Full description

Saved in:
Bibliographic Details
Published in:Computers & operations research 2010, Vol.37 (1), p.62-71
Main Authors: Srirangacharyulu, B., Srinivasan, G.
Format: Article
Language:English
Subjects:
Applied sciences
Completion time variance
Exact sciences and technology
Genetic algorithms
Heuristic
Job shops
Multi-machine scheduling
Operational research and scientific management
Operational research. Management science
Optimization techniques
Production scheduling
Scheduling, sequencing
Single machine scheduling
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper we consider the problem of minimizing the completion time variance of n jobs on a single machine with deterministic processing times. We propose a new heuristic and compare the results with existing popular heuristics for the problem. We also propose a method based on genetic algorithms to solve the problem. We present the worst case performance analysis of the proposed heuristic. We also consider the problem of minimizing the completion time variance of n jobs on m identical parallel machines in both restricted and unrestricted versions. A heuristic method and a method based on genetic algorithms are presented for both the cases and results of computational testing are provided. It is concluded that the proposed methods provide better results compared to existing methods for the single machine case as well as for the multi-machine case.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2009.03.007