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Multi-objective Order Promising for Outsourcing Supply Network of IC Design Houses
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Multi-objective Order Promising for Outsourcing Supply Network of IC Design Houses

James C. Chen, Tzu-Li Chen, Han-Yu Hu, Peter PengTony Lin
IEEE Transactions on Semiconductor Manufacturing
2022

摘要

Costs Heuristic algorithms Hybrid MTS-MTO Integrated circuit modeling Multi-Objective Heuristic Algorithm Multi-stage Order Promising Outsourcing Outsourcing Supply Network Production Semiconductor device modeling Supply chains Electronic Optical and Magnetic Materials Condensed Matter Physics Industrial and Manufacturing Engineering Electrical and Electronic Engineering
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.

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