Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems
A critical machine identification algorithm is proposed for the job shop scheduling problem in which the total tardiness must be minimized. An optimization-based procedure is devised to learn the distribution characteristics of critical machines in a specific scheduling instance. The proposed simulated annealing algorithm optimizes the scheduling problem after the capacity constraints for each machine are modified. A genetic algorithm based on combined dispatching rules is designed to verify the effectiveness of the proposed methodology.
Prasad Yarlagadda, Yun-Hae Kim, Zhijiu Ai and Xiaodong Zhang
R. Zhang "Learning the Distribution Characteristics of Critical Machines in Production Scheduling Problems", Advanced Materials Research, Vol. 337, pp. 142-145, 2011