High-tech industries are experiencing accelerated technological change, which causes rapid obsolescence of invested manufacturing equipment. In such environment, the impact of the new technologies must be carefully considered while making decisions involved in resource acquisition or replacement. In this study, we consider a capacity planning problem with the presence of uncertain magnitude and timing of new technologies and stochastic demands. This study targets of determining (1) the most profitable technology portfolio investment, (2) the corresponding resource levels, and (3) the production plan to fully utilize the capacity. The research problem is modeled by Markov decision process (MDP). The objective is to maximize expected profit under demand and technology uncertainties. For solution efficiency, the Intlinprog solver is utilized to find the optimal action at each decision epoch, accompanying with a parallel computing mechanism to relax the computational burden of the MDP model. Through experiments, we demonstrate the effectiveness of the proposed model, and highlight the importance of considering uncertain factors.

中文翻译：

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需求不确定和技术变化下的战略能力组合规划

高科技产业正在经历加速的技术变革，这导致投资的制造设备迅速淘汰。在这种环境下，在做出涉及资源获取或更换的决策时，必须仔细考虑新技术的影响。在这项研究中，我们考虑了容量规划问题，其中存在不确定的规模和新技术的时机以及随机需求。本研究的目标是确定（1）最有利可图的技术组合投资，（2）相应的资源水平以及（3）充分利用产能的生产计划。研究问题通过马尔可夫决策过程（MDP）建模。目的是在需求和技术不确定性的情况下最大化预期利润。为了提高解决方案的效率，Intlinprog求解器用于在每个决策时期找到最佳动作，并带有并行计算机制以减轻MDP模型的计算负担。通过实验，我们证明了该模型的有效性，并强调了考虑不确定因素的重要性。