权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Simulation-based dynamic heuristic for the distributed optimisation of complex multi-objective multi-project multi-resource production processes

基于仿真的动态启发式复杂多目标多项目多资源生产过程的分布式优化

基本信息

批准号：
223497913
负责人：
Professor Dr. Oliver Rose
金额：
--
依托单位：
Professur für Technische Logistik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2013
资助国家：
德国
起止时间：
2012-12-31 至 2017-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/223497913?language=en
关键词：
Simulation based dynamic heuristic distributed

项目摘要

Decision problems in scheduling and capacity planning exist in many sectors of economy and society. They can be found especially in industrial production but also in construction and healthcare. Typical properties of these problems are their complexity and diversity. The development and production of high-quality machinery, equipment and vehicles has the tendency towards a permanent increase of customer specificity and product diversification whilst product life cycles become shorter at the same time. This leads to extremely complex, non-deterministic and dynamic multi-resource production processes which can hardly be planned and controlled optimally in terms of an efficient production. The issue grows more acute particularly at assembly processes for customer-specific heavy machinery since the number of possible sequence variants increases exponentially due to the overlapping of several factors (e.g., precedence relations, process alternatives, trade-offs between resources etc.). In addition, the objective functions (e.g., cost, time, resource utilisation, etc.) vary job-specifically and may change over time even within an order in such multi-objective problems. Experiences from research and practice show that the effective solution of such problems opens an enormous potential. To date, there are no sufficiently powerful and application flexible models, procedures, and solution methods. Neither exact solution methods, heuristics nor meta-heuristics are currently able to solve these problems satisfactorily.With this basic research project, suitable reference process models and solution methods will be explored which are to be transferable to other application areas with similar problem characteristics. Core objective is the development of concepts respectively architectures and the incorporating methods which are able to solve the described complex problems efficiently and effectively within this structure. The conceptual basic components shall be:- A modular optimisation framework consisting of a generator, optimiser, simulator and analyser- An iterative, heuristic initialisation, optimisation and process concept using agent-similar and meta-heuristic functionalitiesThe key methodological objectives are:- The development of methods for the efficient handling of large search spaces- The exploration of a value system as a method for evaluating and comparing solutions produced under consideration of differentiated objectives and constraints.

调度和能力规划决策问题存在于经济和社会的许多部门。它们尤其可以在工业生产中找到，但也可以在建筑和医疗保健中找到。这些问题的典型特性是它们的复杂性和多样性。高品质机械、设备和车辆的开发和生产有着客户特异性和产品多样化不断增加的趋势，同时产品生命周期也在缩短。这导致了极其复杂的、不确定的和动态的多资源生产过程，这些生产过程很难在有效生产方面进行最佳规划和控制。这个问题变得更加尖锐，特别是在客户特定重型机械的组装过程中，因为可能的序列变体的数量由于几个因素的重叠而呈指数级增加（例如，优先关系、工艺选择、资源之间的权衡等）。此外，目标函数（例如，成本、时间、资源利用等）在这种多目标问题中，由于工作的特殊性而变化，甚至在一个顺序内也可能随时间而变化。研究和实践的经验表明，有效解决这些问题具有巨大的潜力。到目前为止，还没有足够强大和应用灵活的模型，程序和解决方案。目前无论是精确解方法、数学方法还是元数学方法都不能很好地解决这些问题，本研究将探索适合的参考过程模型和求解方法，并将其应用于具有类似问题特征的其他应用领域。核心目标是概念的发展，分别架构和结合的方法，能够有效地解决所描述的复杂问题，有效地在这个结构。概念上的基本组成部分应该是：-一个模块化的优化框架，包括一个生成器，优化器，模拟器和分析器-一个迭代的，启发式的初始化，优化和过程的概念，使用代理类似和元启发式的功能关键方法的目标是：-方法的发展，有效地处理大搜索空间-价值系统的探索，作为一种方法，用于评估和比较的解决方案，考虑到差异化的目标和约束。