Abstract: The solution of the Machines’ Time Scheduling Problem (MTSP) is a hot point of research that is not yet matured, and needs further work. This paper presents two algorithms for the solution of the Machines’ Time Scheduling Problem that leads to the best starting time for each machine in each cycle. The first algorithm is genetic-based (GA) (with non-uniform mutation), and the second one is based on particle swarm optimization (PSO) (with constriction factor). A comparative analysis between both algorithms is carried out. It was found that particle swarm optimization gives better penalty cost than GA algorithm and max-separable technique, regarding best starting time for each machine in each cycle.

Ghoniemy S, El-sawy A. A., Shohla M. A. and Gihan E. H.  Ali, “ The Solution of Machines’ Time Scheduling Problem Using Artificial Intelligence Approaches” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(1), 2012. http://dx.doi.org/10.14569/IJARAI.2012.010111

@article{S2012,
title = { The Solution of Machines’ Time Scheduling Problem Using Artificial Intelligence Approaches},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2012.010111},
url = {http://dx.doi.org/10.14569/IJARAI.2012.010111},
year = {2012},
publisher = {The Science and Information Organization},
volume = {1},
number = {1},
author = {Ghoniemy S and El-sawy A. A. and Shohla M. A. and Gihan E. H.  Ali}
}