Modeling of a hyperheuristic approach within an agent system to support operational planning for industrial product service systems in the production environment

对代理系统内的超启发式方法进行建模，以支持生产环境中工业产品服务系统的运营规划

• 批准号: 424733996
• 负责人: Professor Dr.-Ing. Bernd Kuhlenkötter
• 金额: --
• 依托单位: Lehrstuhl für Produktionssysteme
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/424733996?language=en
• 关键词: Modeling; hyperheuristic; approach; within; agent

Industrial Product Service Systems (IPS²) offer an opportunity for manufacturing enterprises to offer customized solutions. The basis for the high quality and punctual delivery of IPS² is therefore an efficient short-term (operative) planning. Within the scope of this operative planning, the priority, the execution time and the required qualification and equipment of the service to be planned must be taken into account. In addition, information about the partners in the network is also relevant, in particular about the personnel employed for the provision of services. In addition, information about the personnel involved in the provision of the services is also relevant during planning. The dispatcher is responsible for aggregating this information in the context of operative planning, taking into consideration target parameters such as cost-minimized route planning, high technical utilization and on-time delivery. To support the dispatcher, various software solutions are presently available. However, these do not manage to generate a planning result that takes into account the multitude of relevant information as well as the specific characteristics of the respective IPS² type.The aim of the project is therefore to develop a methodical approach for a decision support system that takes into account the information relevant to the operative planning process, such as the various IPS² types existing in a provider network, and leaves the planner room for personal assessments within the framework of decision making. Since operative performance planning in the context of IPS² is a multi-criteria planning problem that cannot be solved polynomially, a hyperheuristic approach is chosen here. Hyper-heuristics used simpler meta-heuristics and heuristics, so-called low-level heuristics, to solve the planning problem. As a result of this hybridisation, the strengths of individual low-level methods are exploited for specific application areas and their weaknesses are compensated for by other methods. Low-level heuristics suitable for this context will be determined within the framework of the project and the corresponding hyperheuristic will be developed. In this context, the previously selected low-level heuristics are executed by different agents and their deployment is controlled by a superordinate coordinating "hyperheuristic" agent. By using an agent-based approach, the flexibility of the planning tool is increased. Resources and participants of the IPS² network can be mapped by autonomous agents and thus possibly necessary adaptations, such as the integration of further network participants during runtime, can be facilitated. By adapting the boundary conditions of hyper heuristics, the dispatcher also has the opportunity to bring his or her experience into the planning process.

工业产品服务系统（IPS²）为制造企业提供了提供定制解决方案的机会。因此，IPS²的高质量和注射性交付的基础是有效的短期（手术）计划。在此操作计划的范围内，必须考虑到计划的优先级，执行时间和所需的资格和设备。此外，有关网络合作伙伴的信息也很重要，特别是有关提供服务的人的信息。此外，有关在计划期间，有关提供服务的人的信息也很重要。考虑到目标参数，例如成本最小的路线计划，高技术利用和按时交付，调度员负责在操作计划的背景下汇总此信息。为了支持调度员，提供了各种软件解决方案。但是，这些并不设法产生计划结果，该计划考虑了许多相关信息以及相应IPS²类型的特定特征。因此，该项目的目的是为决策支持系统开发一种有方法的方法，该方法考虑了与操作计划过程相关的信息，例如在提供者网络中现有的各种IPS领域，以及在计划室中存在的各种IPS领域，以及在计划室内进行个人评估范围内的框架，以实现个人评估。由于在IPS²的背景下的操作绩效计划是无法在多项式上解决的多标准计划问题，因此在这里选择了一种超声处理方法。超高术使用了更简单的元数据术和启发式方法，即所谓的低级启发式方法来解决计划问题。由于这种杂交的结果，针对特定的应用领域利用了单个低级方法的优势，而其弱点是通过其他方法来补偿的。适用于这种情况的低级启发式方法将在项目框架内确定，并将开发相应的过高手术。在这种情况下，先前选择的低水平启发式方法由不同的代理执行，其部署由上级协调“超高”代理控制。通过使用基于代理的方法，可以提高计划工具的灵活性。 IPS²网络的资源和参与者可以由自主代理绘制，因此可能需要进行必要的适应，例如可以准备进一步的网络参与者在运行时集成。通过调整超级启发式的边界条件，调度员还有机会将其经验带入计划过程。