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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.
Time, cost and quality are the key attributes of cloud manufacturing services, and are also the core elements that affect the user’s credit rating of cloud manufacturing service portfolio. In order to make the cloud manufacturing service portfolio better meet the needs of users, a comprehensive creditworthiness-based Cloud manufacturing service composition algorithm.The algorithm derives the creditworthiness of the service portfolio from the user’s emphasis and expectation on the time, cost and quality attributes, and achieves the goal of multi-objective optimization by adjusting the attribute weight value.This algorithm is based on the artificial bee colony algorithm (Artificial Bee Colony algorithm, ABC), and introduces the tabu search idea to improve it. Firstly, the paper analyzes the main evaluation indexes of cloud manufacturing service quality and establishes the credit function of cloud manufacturing service portfolio as the fitness function of ABC food source. Secondly, And the requirements of service requesters are used as the constraints of the algorithm.Finally, tabu search is introduced into ABC algorithm to improve the algorithm.Experiments show that this algorithm is feasible in the cloud manufacturing service portfolio.