@inproceedings{95594f6e4b5d4beba06b9b61f061ae69,
title = "Joint optimization of delivery constraint and capacity adjustment for electronic component production system",
abstract = "To keep competitive in the new dynamic market having more requirements in product various and delivery date, manufacturing companies need to make systems that not only response to market rapidly but also ensure delivery on time. Reconfigurable manufacturing system is a new paradigm to enhance the ability to response to the market rapidly and improve the performance rate. Capacity scalability is an important feature for reconfigurable manufacturing system. The effectiveness of an RMS depends on production scheduling and the time to reconfigure. According to the theory of constrains, bottleneck is the main factor to hinder the development of a manufacturing system. So the schedule and the adjustment of production capacity for bottleneck are really important in improving a manufacturing system performance. This paper focuses on the scheduling of bottleneck which can adjust production capacity and develops a model to solve this type problem. An adaptive genetic algorithm is used to solve the model. The aim of the problem is to find out the best schedule and device production capacity. Finally, an example is used to validate the results of the model and its solution procedure.",
keywords = "capacity adjustment, genetic algorithm, joint optimization, tardiness penalty",
author = "Yu Guan and Yaoguan Hu and Rui Zhou",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 ; Conference date: 05-06-2016 Through 07-06-2016",
year = "2016",
month = oct,
day = "19",
doi = "10.1109/ICIEA.2016.7603687",
language = "English",
series = "Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "779--783",
booktitle = "Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016",
address = "United States",
}