Planning of the diversity of industrial portfolios - Complexity-based decision making model by means of evolutionary algorithms

该研究项目的目标是开发一个基于复杂性的决策模型，用于规划工业制造商的投资组合。因此，在考虑客户的成本和支付意愿的同时，应考虑公司的目标，如利润或收入最大化。本研究项目的研究对象分为两个层次。一方面考虑工业产品服务系统(由技术产品和工业服务组成)，另一方面考虑工业投资组合(由所提供的产品服务系统之和组成)。通过向客户提供工业产品服务系统，公司如今可以从竞争对手中脱颖而出。研究对象的复杂性取决于所提供的解决方案的多样性和多样性，以及它们之间的相互依存关系和市场动态，这促使公司不断地根据客户的需求调整解决方案。通过所开发的解释模型，可以全面了解投资组合的多样性首先对内部流程和资源产生的影响，然后是对投资组合的变化驱动成本的影响。基于客户支付意愿的解释模型和现有预测模型，应以优化的产业组合多样性的形式确定解决方案在市场上的价值和内部引起的成本的最佳可能程度。由于这一研究问题有大量可能的可供选择的解，因此将采用基于进化算法的启发式优化方法。通过使用决策模型，应选择工业投资组合的优化多样性的稳健结果。

The goal of the research project is to develop a complexity based decision making model for planning the portfolio of industrial manufacturers. Thereby corporate goals such as profit- or revenue-maximisation while considering costs and willingness to pay of the customers shall be taken in to account. The object of the research project is subdivided in to two levels. On the one hand industrial product service systems (consisting of technical products and industrial services) and on the other hand industrial portfolios (consisting of the sum of offered product service systems) are regarded. By offering industrial product service systems to their customers companies can nowadays differentiate from their competitors. The complexity of the object of research submits to the variety and diversity of the offered solutions and their interdependency as well as to the market dynamics, which drives companies to continuously adapt the solutions to the customers needs. By means of the developed explanatory model a comprehensive understanding of the effects that variety of the portfolio has firstly on internal processes and resources and therefor secondly on the variety driven costs of the portfolios shall be gained. Based on the explanatory model and existing forecast models for willingness to pay of the customers, a best possible degree of the value of the solutions on the market and the internal caused costs shall be determined in forms of an optimized diversity of industrial portfolios. Due to the huge number of possible alternative solutions for this research problem a heuristic based optimization approach by means of evolutionary algorithms will be employed. By use of a decision making model robust results for the optimized diversity of industrial portfolios shall be selected.