摘要
Research and development (R&D) projects are crucial for semiconductor companies to maintain growth, profitability, and competitiveness. Integrated circuit (IC) design is capital intensive and continuously migrates to new technologies to meet various market demands. Moreover, the scheduling of selected R&D projects that enables technology roadmap involving complicated interrelationships, while competing for similar resources. Focusing on realistic needs, this paper aims to propose an integrated approach for selecting IC design projects for R&D portfolios and scheduling the selected projects simultaneously. In particular, a hybrid autotuning multiobjective genetic algorithm was developed to solve large sized problem instances. An empirical study was conducted at a leading IC design service company in Taiwan to test the validity of the proposed approach. The proposed algorithm was compared with conventional approaches for both convergence and diversity. The results have shown the practical viability of this approach in efficiently and effectively generating near-optimal portfolio alternatives for portfolio selection. The approach also enables the scheduling of the selected projects to achieve R&D portfolio objectives. The developed solution was fully implemented and adopted by the company.