Abstract
This article proposes a genetic algorithm approach to minimize total flow time of a set of tasks for identical parallel machines and worker assignment to machines. A spreadsheet-based domain independent general purpose genetic algorithm (GA), an add-in to the spreadsheet software, is used to solve the problem. The paper demonstrates an adaptation of the proprietary GA software to the problem of minimizing total flow time for the worker assignment scheduling problem for identical parallel machine models. Two 100
I
/
P
/
n
/
m
/
W
problems taken from Hu (Int J Adv Manuf Technol 25:1046–1052,
2005
, 29:753–757,
2006
). The performance of GA is superior to SPT-A/LMC approach used by Hu. As compared to Hu, the proposed GA finds optimal solution for all 100
I
/
P
/
6
/
3
/
10
problems and for 99 problems out of the 100
I
/
P
/
12
/
3
/
10
problems.