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Constraint-based genetic algorithms for machine requirement of semiconductor assembly industry : a proposed framework

Yusof, Umi Kalsom and Deris, Safaai (2009) Constraint-based genetic algorithms for machine requirement of semiconductor assembly industry : a proposed framework. In: Proceedings - 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009. Article number 5071953 . Institute of Electrical and Electronics Engineers, New York, pp. 29-34. ISBN 978-076953648-4

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Official URL: http://dx.doi.org/10.1109/AMS.2009.119

Abstract

Having an accurate capacity planning is always an ultimate goal for semiconductor manufacturing. However, as capacity planning is highly affected by the demand forecast uncertainty, there is a necessity to make the gap closer to ensure profitability. The paper defines the problems faced by a semiconductor company in handling capacity planning and balancing the capital investment cost against the risk of losing revenue. Machine allocation in capacity planning is a process to determine mixture of a machine types that satisfy all precedence and resource constraints and minimize the total machines allocation. We adopt constraint-based genetic algorithm (GA) to solve this optimization problem with the focus on mapping the right chromosome representation to the domain problem. The method is chosen to allow the running of GA in original form as well as to ensure the computation is straight forward and simple.

Item Type:Book Section
Uncontrolled Keywords:machine allocation, machine requirements, optimization problems, resource constraint, semiconductor assembly, semiconductor companies
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:13276
Deposited By: Ms Zalinda Shuratman
Deposited On:02 Aug 2011 04:38
Last Modified:02 Aug 2011 04:38

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