Variable Neighborhood Search Approaches for Correlated Parallel Machine Scheduling Problems  
Author Y.K. Lin




Abstract In this research, we study the problem of scheduling parallel machines with release time to minimize total weighted tardiness. We consider different levels and combinations of machine correlation and job correlation in the processing times. A mathematical model is applied to classify the difficulty of each machine correlation and job correlation environment. Also, four different variations of the variant neighborhood search (VNS) algorithm have been applied to solve the studied problem. Computational results show that as the correlations get higher, the problem instances become harder for the mathematical model to solve. Also, the computation results show that the machine correlation and job correlation both influence the performance and computation time of the VNS algorithms.


Keywords scheduling, parallel machines, correlation, release time, total weighted tardiness, variant neighborhood search
    Article #:  22259
Proceedings of the 22nd ISSAT International Conference on Reliability and Quality in Design
August 4-6, 2016 - Los Angeles, California, U.S.A.