【摘要】 时间、成本和质量是云制造服务的关键属性,也是影响用户对云制造服务组合信誉度评价的核心要素,为了使云制造服务组合更好地满足用户的需要,提出一种基于综合信誉度的云制造服务组合算法.算法从用户对时间、成本和质量等属性的重视度和期望值综合得出服务组合的信誉度,通过调整属性权重值达到多目标优化的目的.本文算法基于人工蜂群算法(Artificial Bee Colony algorithm,ABC),并引入禁忌搜索思想加以改进:首先,分析云制造服务质量主要评价指标,建立云制造服务组合的信誉度函数作为ABC算法食物源的适应度函数;其次,把服务需求者的需求条件作为算法约束条件;最后,在ABC算法中引入了禁忌搜索的思想进行改进.实验表明,本算法在云制造服务组合具有较好的可行性.更多还原

【Abstract】 In order to make the cloud manufacturing service composition more reasonable that can better meet users’ needs,this paper proposes a new method of cloud manufacturing service composition based on reputation degree. The reputation degree of a certain cloud manufacturing service composition can be calculated by comparing the theoretical values of the time,cost and quality features with the expected values that users desiring on the features,that are adjusted by weight values that user gives. The core of the algorithm is an improved artificial bee colony algorithm. Firstly,building reputation degree function as fitness function of food source in the ABC algorithm. Secondly,inputting the service requirements as the constraint condition of the algorithm. Finally,the ABC algorithm is improved by introducing the idea of tabu search. Experiment results show that this algorithm is feasible in cloud manufacturing service composition.更多还原