|United States Patent||5,319,781|
|Syswerda||Jun. 7, 1994|
|Inventors:||Syswerda; Gilbert P. (Winchester, MA).|
|Assignee:||Bolt Beranek and Newman Inc. (Cambridge, MA).|
|Filed:||May 3, 1991|
|Intl. Cl.:||G06F 15/00; G06F 9/00|
|U.S. Cl.:||395/650; 364/DIG.1; 364/281.8; 364/281.3|
|Field of Search:||395/650; 364/DIG. 1, 281.3, 281.8|
|5,148,513||Sept., 1992||Koza et al.||395/ 13|
"A Genetic Algorithm for job shop", Falkenauer, E., and Bouffouix, S., Proc. of 1991 IEEE Int. Conf. on Robotics & Aut. Sacramento, Calif. Apr. 1991, pp. 824-829.
"Efficient Multiprocessor Scheduling Based on Genetic Algorithms", Hou, E. S., Hong, R. and Ansari, N. pp. 1239-1243.
In the scheduling method disclosed herein, a genetic algorithm is employed to improve a population of possible schedules represented by respective chromosomes, where the chromosomes upon which the genetic algorithm operates are not a direct encoding of a possible schedules. Rather, the details of the scheduling problem and the real life constraints typically associated with such problems are hidden from the genetic algorithm by the use of a deterministic schedule builder which operates on lists of the desired tasks and which generates legal schedules, i.e. schedules which do not violate hard constraints. The legal schedules so generated are evaluated or scored and the scores are provided to the genetic algorithm as feedback for influencing subsequent operation of the genetic algorithm.