Optimization Based-on Genetic Algorithms of Job-employee Scheduling in Agricultural Mechanization Research

Job-employee scheduling problem in agricultural mechanization research has been known as NP-hard problem. The Job-employee scheduling problem allows one task to be implemented by several agricultural technicians out of a team. The problem is to assign each task to a technician and find a sequence for the tasks on the technician in order that the completion time of all tasks is minimized. A HGA based on taboo search and new two-chromosome encoding scheme is presented for scientific decision of this problem. Finally, an example is simulated in MATLAB7.0.