Title :
A heuristic genetic algorithm for flowshop scheduling
Author :
Chakraborty, Uday K. ; Lah, D. ; Chakraborty, Mandira
Author_Institution :
Dept. of Math. & Comput. Sci., Missouri Univ., St. Louis, MO, USA
Abstract :
Flowshop scheduling deals with determining the optimum sequence of jobs to be processed on several machines so as to satisfy some scheduling criterion. It is NP-complete. Heuristic algorithms use problem-specific information to yield a good working solution. Genetic algorithms are stochastic, adaptive, general-purpose search heuristics based on concepts of natural evolution. We have developed a new heuristic genetic algorithm (NGA) which combines the good features of both the GA and heuristic search. The NGA is run on several problems and its performance is compared with that of the conventional genetic algorithm and the well-known NEH heuristic. The NGA is seen to perform better in almost all instances.
Keywords :
computational complexity; genetic algorithms; heuristic programming; scheduling; search problems; NEH heuristic; NGA; NP-complete; flowshop scheduling; heuristic genetic algorithm; heuristic search; job processing; natural evolution; optimum sequence; problem-specific information; scheduling criterion; stochastic adaptive general-purpose search heuristics; Computer science; Evolution (biology); Genetic algorithms; Genetic mutations; Heuristic algorithms; Mathematics; Mechanical engineering; Polynomials; Processor scheduling; Stochastic processes;
Conference_Titel :
Information Technology Interfaces, 2001. ITI 2001. Proceedings of the 23rd International Conference on
Print_ISBN :
953-96769-3-2
DOI :
10.1109/ITI.2001.938035
