Document Type
Thesis
Date of Award
8-30-1991
Degree Name
Master of Science in Electrical Engineering - (M.S.)
Department
Electrical and Computer Engineering
First Advisor
Edwin Hou
Second Advisor
Nirwan Ansari
Third Advisor
Sotirios Ziavras
Abstract
The problem of multiprocessor scheduling can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. This scheduling problem in known to be NP-hard and methods based on heuristic search have been proposed to obtain optimal and sub-optimal solutions to the problem. Genetic algorithms have recently received much attention as robust stochastic searching algorithms for various optimization problems. In this thesis, we propose an efficient method based on genetic algorithms to solve the multiprocessor scheduling problem. The representation of the search node will be based on the schedule of the tasks in each individual processor. The genetic operator proposed is based on the precedence relations between the tasks in the task graph. The proposed genetic algorithms will be applied to the problem of scheduling the robot inverse dynamics computations and randomly generated task graphs.
Recommended Citation
Ren, Hong, "Efficient multiprocessor scheduling based on genetic algorithms" (1991). Theses. 2605.
https://digitalcommons.njit.edu/theses/2605
