摘要
针对制造业从生产型转变为服务型给新时代制造业带来的影响,分析了定制产品在云制造环境下给企业带来的制造资源不足问题,提出了面对多个复杂制造任务的多服务组合形式,以提高制造服务资源利用率。建立了以时间、成本、能耗、可靠性、可用性5个因素为属性指标的服务质量(Quality of Service, QoS)评价模型,再引入一种基于涡流搜索算法(Vortex Search algorithm, VS)和人工蜂群算法(Artificial Bee Colony algorithm, ABC)的混合搜索算法,给出了该算法与优化问题的映射关系,在全局搜索中实现局部搜索,确保了问题求解的寻优精度。以汽车个性化定制生产任务为例,验证了优化模型的有效性和VS-ABC算法可行性。结果表明,与传统涡流搜索算法、人工蜂群算法相比,VS-ABC算法具有更快收敛速度和适用性。
In this article, in view of the impact of the manufacturing industry’s shift from production orientation to service-orientation in this new era, efforts are made to analyze the manufacturing resource shortage caused by customized products in the context of cloud manufacturing. In order to improve the utilization rate of manufacturing service resource, multi-service composition is proposed, which is targeted to multiple complex manufacturing tasks. The Quality of Service(QoS) evaluation model is constructed, with time, cost, energy consumption, reliability, and availability as the attribute indexes. The hybrid search algorithm based on the Vortex Search algorithm(VS) and the Artificial Bee Colony algorithm(ABC) is introduced to work out the mapping relationship between the algorithm and the optimization problem, which has realized local search in global search and ensured optimized precision of problem solving. The effectiveness of the optimization model and the feasibility of the VS-ABC algorithm are verified by means of the automobile customized products. These results show that the VS-ABC algorithm has faster speed and more desirable applicability in terms of convergence and running time, compared with the traditional eddy current search algorithm and the artificial bee colony algorithm.
作者
梁迪
王杰一
程璎珞
LIANG Di;WANG Jie-yi;CHENG Ying-luo(School of Mechanical Engineering,Shenyang University,Shenyang 110044)
出处
《机械设计》
CSCD
北大核心
2022年第5期63-71,共9页
Journal of Machine Design
