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引用次数: 3
摘要
在当今高度不稳定的制造业市场,公司每天都面临着重要的战略决策,例如“公司是否有必要的能力接受大量订单?”或者“如果产品需求每年增长x%,需要采取什么措施?”决策者,即公司的经理,依靠他们的经验和洞察力,由经典工具支持,做出这样的决定。经典的数学求解器或基于代理的系统是实现战略规划工具的典型体系结构解决方案,以支持决策者执行这一重要任务。在ARUM (Adaptive Production Management)项目中,设计并开发了一种混合战略规划工具,将经典求解器的优化特性与智能体系统的灵活性和敏捷性相结合。本文简要介绍了这种架构,并重点讨论了“假设游戏”机制的生成,以支持更智能和动态的规划解决方案的生成。
What-if game simulation in agent-based strategic production planners
In the nowadays highly unstable manufacturing market, companies are faced, on a daily basis, with important strategic decisions, such as “does the company has the necessary capacity to accept a high volume order?” or “what measures need to be implemented if the product demand increases x% a year?”. Decision-makers, i.e. company's managers, rely on their experience and insights supported by classical tools to take such decisions. Classical mathematical solvers or agent-based systems are typical architectural solutions to implement strategic planning tools to support decision-makers on this important task. Within the ARUM (Adaptive Production Management) project, a hybrid strategic planning tool was specified and developed, combining the optimization features of classical solvers with the flexibility and agility of agent systems. This paper briefly presents such architecture and focuses on the generation of the “what-if game” mechanism to support the generation of more intelligent and dynamic planning solutions.