The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.05 - October (1995 vol.10)
pp: 60-67
ABSTRACT
This article describes a feasible approach to solve large-scale and real-world scheduling problems. Assuming that a problem can be divided into several subproblems, our approach applies different optimization methods to different classes of subproblems. This fundamental idea is realized in a scheduling problem solver that provides a variety of useful optimization methods, including rule-base systems and genetic algorithms. To show the solver's feasibility, we applied it to a scheduling problem that occurs in the steelmaking process. Finally, we discuss some future directions of the solver.
INDEX TERMS
rule-based expert system, genetic algorithms, operations research, process scheduling, steelmaking process
CITATION
Kazuro Hamada, Toshimitsu Baba, Ken?ichi Sato, Masanao Yufu, "Hybridizing a Genetic Algorithm with Rule-Based Reasoning for Production Planning", IEEE Intelligent Systems, vol.10, no. 5, pp. 60-67, October 1995, doi:10.1109/64.464934
5 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool