TY - GEN
T1 - A job shop scheduling approach based on simulation optimization
AU - Yan, Yan
AU - Wang, Guoxin
PY - 2007
Y1 - 2007
N2 - With regards to the problem of the traditional scheduling approach can't establish the precise scheduling models and obtain the satisfied scheduling results at the same time, a new scheduling approach based on simulation optimization methodology is presented. The approach comprises two modules: genetic algorithm (GA) based optimizer and discrete event simulation model. Candidate scheduling schemes represented by a serial of scheduling rules are suggest by GA that automatically guides the system towards better solutions. Simulation models are used to evaluate the performance of candidate scheduling schemes, the results of evaluation are returned to the GA to be utilized in selection of the next generation of candidate scheduling schemes to be evaluated. This process continues until a satisfactory solution is obtained. In addition, In order to build simulation model rapidly for the similar production conditions, a simulation modeling approach based on modular control models including shop level controller model, cell level controller model and equipment level controller model is present. The approach encompasses control logic, which are separated from the basic modeling elements in the simulation model, of different levels in production system. Finally, a case study is presented to illustrate the application of the proposed approach.
AB - With regards to the problem of the traditional scheduling approach can't establish the precise scheduling models and obtain the satisfied scheduling results at the same time, a new scheduling approach based on simulation optimization methodology is presented. The approach comprises two modules: genetic algorithm (GA) based optimizer and discrete event simulation model. Candidate scheduling schemes represented by a serial of scheduling rules are suggest by GA that automatically guides the system towards better solutions. Simulation models are used to evaluate the performance of candidate scheduling schemes, the results of evaluation are returned to the GA to be utilized in selection of the next generation of candidate scheduling schemes to be evaluated. This process continues until a satisfactory solution is obtained. In addition, In order to build simulation model rapidly for the similar production conditions, a simulation modeling approach based on modular control models including shop level controller model, cell level controller model and equipment level controller model is present. The approach encompasses control logic, which are separated from the basic modeling elements in the simulation model, of different levels in production system. Finally, a case study is presented to illustrate the application of the proposed approach.
KW - Genetic algorithm
KW - Scheduling
KW - Simulation modeling
KW - Simulation optimization
UR - http://www.scopus.com/inward/record.url?scp=40649103182&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2007.4419506
DO - 10.1109/IEEM.2007.4419506
M3 - Conference contribution
AN - SCOPUS:40649103182
SN - 1424415292
SN - 9781424415298
T3 - IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management
SP - 1816
EP - 1822
BT - IEEM 2007
T2 - 2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007
Y2 - 2 December 2007 through 4 December 2007
ER -