Genetic algorithms for flowshop scheduling problems
Computers and Industrial Engineering
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
A combinatorial particle swarm optimisation for solving permutation flowshop problems
Computers and Industrial Engineering
A Constructive Genetic Algorithm for permutation flowshop scheduling
Computers and Industrial Engineering
Computers and Operations Research
Computers and Operations Research
CSCWD '09 Proceedings of the 2009 13th International Conference on Computer Supported Cooperative Work in Design
Expert Systems with Applications: An International Journal
Hybridizing VNS and path-relinking on a particle swarm framework to minimize total flowtime
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
This paper presents a new Variable Neighborhood Search (VNS) approach to the permutational flowshop scheduling with total flowtime criterion, which produced 29 novel solutions for benchmark instances of the investigated problem. Although many hybrid approaches that use VNS do exist in the problems literature, no experimental study was made examining distinct VNS alternatives or their calibration. In this study six different ways to combine the two most used neighborhoods in the literature of the problem, named job interchange and job insert, are examined. Computational experiments were carried on instances of a known dataset and the results indicate that one of the six tested VNS methods, named VNS4, is quite effective. It was compared to a state-of-the-art evolutionary approach and statistical tests applied on the computational results indicate that VNS4 outperforms its competitor on most benchmark instances.