Computers and Industrial Engineering
Multiobjective Scheduling by Genetic Algorithms
Multiobjective Scheduling by Genetic Algorithms
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Multi-plant production scheduling in SMEs
Robotics and Computer-Integrated Manufacturing
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
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Multilevel production scheduling problem is a typical combinatorial optimization problem in a manufacturing system, which is traditionally modeled as several hierarchical sublevel problems and optimized at each level, respectively. An integrated model, which can cope with the whole multilevel scheduling information simultaneously, is proposed in this paper, and a specific evolutionary algorithm is designed to solve the integrated model with a twin-screw coding strategy. In order to evaluate the performance of the new algorithm, a real 3-level production scheduling problem is employed for case study, and two typical metaheuristic algorithms, a genetic algorithm (GA) and a simulated annealing (SA), are also employed for comparison study. Experimental simulation results show that our proposed modeling and optimization method has outperformed the other ones.