Computer simulation aids for the intelligent manufacture of quality clothing
Computers in Industry
Genetic algorithms for sequencing problems in mixed model assembly lines
Computers and Industrial Engineering
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Computers and Industrial Engineering
Handbook of Dynamic System Modeling (Cpaman & Hall/Crc Computer and Information Science)
Handbook of Dynamic System Modeling (Cpaman & Hall/Crc Computer and Information Science)
A mathematical model and a genetic algorithm for two-sided assembly line balancing
Computers and Operations Research
Intelligent production control decision support system for flexible assembly lines
Expert Systems with Applications: An International Journal
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Assembly line balancing problem with deterioration tasks and learning effect
Expert Systems with Applications: An International Journal
A study of assembly line balancing problem in clothing manufacturing by simulation
ASM '07 The 16th IASTED International Conference on Applied Simulation and Modelling
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper investigates the operator allocation problems (OAP) with jobs sharing and operator revisiting for balance control of a complicated hybrid assembly line which appears in the apparel sewing manufacturing system. Multiple objectives and constraints for the problem are formulated. The utility function is employed to deal with the difficulty of combining several conflicting and incommensurable objectives into one overall measure. An optimization model combining the Pareto utility discrete differential evolution (PUDDE) algorithm and the embedded discrete event simulation (DES) model is proposed to solve the OAPs. The PUDDE algorithm is an improved discrete differential evolution approach used with the Pareto utility selection strategy, which extends the real-value differential evolution to handle the discrete-value vector by introducing two modified operators, namely the subtraction and addition operators. During the optimization process, the embedded DES model is used to evaluate the performance objectives by analyzing the dynamic behaviors of the hybrid assembly lines, which tackles the problem of having no closed-form mathematical expressions for the evaluation of performance objectives owing to the existence of jobs sharing and operator revisiting. Extensive experiments are conducted to validate the proposed optimization model. The experimental results demonstrate that the proposed PUDDE-based optimization model can effectively solve the OAPs for the hybrid assembly lines with the consideration of jobs sharing and operator revisiting. It was also found that the proposed PUDDE algorithm evidently outperforms the general differential evolution algorithm. Compared with the collected industrial results, the solution generated by the proposed optimization model has much better performance objectives for the hybrid assembly lines.