Multiobjective Order Promising for Outsourcing Supply Network of IC Design Houses

To decide which orders to be accepted for an IC design house, besides wafers and capacity, several factors also need to be considered, including product flexibility, minimal cost path, order delay cost, and the fairness of order fulfillment rate between customers. This research focuses on a multi-ob...

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Vydáno v:IEEE transactions on semiconductor manufacturing Ročník 35; číslo 4; s. 680 - 697
Hlavní autoři: Chen, James C., Chen, Tzu-Li, Hu, Han-Yu, Peng, Peter, Lin, Tony
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.11.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Costs
Customers
Design of experiments
Flexibility
Heuristic algorithms
Heuristic methods
hybrid MTS-MTO
Integer programming
Integrated circuit modeling
Integrated circuits
Mixed integer
multi-objective heuristic algorithm
Multi-stage order promising
Multichip modules
Order processing
Outsourcing
outsourcing supply network
Production
Semiconductor device modeling
Supply chains
Variance analysis
ISSN:0894-6507, 1558-2345
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Popis
Shrnutí:To decide which orders to be accepted for an IC design house, besides wafers and capacity, several factors also need to be considered, including product flexibility, minimal cost path, order delay cost, and the fairness of order fulfillment rate between customers. This research focuses on a multi-objective order promising problem for the hybrid MTS-MTO outsourcing supply network of an IC design house. The objectives are to maximize total profit, minimize total delay cost of accepted orders, and minimize the discrepancy of order fulfillment rate between customers. The multi-stage and multi-site outsourcing supply network, technical capacity constraints, product flexibility and multi-chip module are considered. This problem is modeled with a multi-objective mixed integer programming model. A heuristic algorithm, called the fairness-based multi-objective order promising algorithm (FMOPA) with four modes is developed to solve the problem. Moreover, experimental design is conducted to evaluate the efficiency of the proposed model with various factors and levels. Analysis of variance (ANOVA) is used to evaluate the factors in accordance to the objectives. The optimal algorithm mode under thirty-two combinations of different environment factors are also evaluated. This can assist decision makers to use the optimal algorithm mode to generate the best favorable result under different environment factors.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0894-6507
1558-2345
DOI:10.1109/TSM.2022.3200128