NDLI: Constraint-Based Genetic Algorithms for Machine Requirement of Semiconductor Assembly Industry: A Proposed Framework

Content Provider	IEEE Xplore Digital Library
Author	Yusof, U.K. Deris, S.
Copyright Year	2009
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.
Starting Page	29
Ending Page	34
File Size	272237
Page Count	6
File Format	PDF
ISBN	9781424441549
DOI	10.1109/AMS.2009.119
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-25
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Profitability Demand forecasting Genetic Algorithm Genetic algorithms Manufacturing industries Investments Capacity Planning Optimization Approach Machine Allocation Semiconductor device manufacture Resource management Assembly Capacity planning
Content Type	Text
Resource Type	Article

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