Sequencing to minimize work overload in assembly lines with product options
Management Science
Sequencing mixed-model assembly lines with genetic algorithms
Computers and Industrial Engineering
A hybrid GA-SA algorithm for just-in-time scheduling of multi-level assemblies
Computers and Industrial Engineering
Algorithms for sequencing mixed models on an assembly line in a JIT production system
Computers and Industrial Engineering
A genetic alorithm for multiple objective sequencing problems in mixed model assembly lines
Computers and Operations Research
A note on Toyota's goal of sequencing mixed models on an assembly line
Computers and Industrial Engineering
An evolutionary approach to multi-objective scheduling of mixed model assembly lines
Computers and Industrial Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Determining numbers of workstations and operators for a linear walking-worker assembly line
International Journal of Computer Integrated Manufacturing
Mixed model assembly line balancing problem with fuzzy operation times and drifting operations
Proceedings of the 40th Conference on Winter Simulation
International Journal of Systems Science
The mixed-product assembly line sequencing problem of a door-lock company in Taiwan
Computers and Industrial Engineering
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In this paper the human resource management in manual mixed model assembly U-lines is considered. The objective is to minimise the total conveyor stoppage time to achieve the full efficiency of the line. A model, that includes effects of the human resource, was developed in order to evaluate human factor policies impact on the optimal solution of this line sequencing problem. Different human resource management policies are introduced to cope with the particular layout of the proposed line. Several examples have been proposed to investigate the effects of line dimensions on the proposed management policies. The examples have been solved through a genetic algorithm. The obtained results confirm the effectiveness of the proposed model on the performance optimisation of the line.