摘要 通过多目标多属性决策方法，解决基于服务质量(quality of service, QoS)的大规模Web服务选择和组合问题。不同于以往将多个QoS值赋权累加为单一值的方法，采用多属性决策方法，同时处理多个QoS属性，将每个解到正负理想点的距离转化为多目标优化问题。提出一种基于ε支配的多目标遗传算法来解决Web服务组合优化问题。计算结果为一组折中的帕累托最优解集，为用户提供多种选择方案。当用户所选择的服务运行失败时，用户可以从其他备选服务中进行选择。实验结果表明，所提出算法具有满意的收敛性、分布性和可扩展性，且算法复杂性优于流行算法NSGA-II和SPEA2。
Abstract：Through the method of multi-objective and multi-attribute decision, this paper solves the problem of QoS (quality of service)-oriented large scale Web service selection and composition. It differs from the traditional method which aggregates all QoS values into a single value. This paper treats all QoS attributes simultaneously by using the multi-attribute decision making method and employs a multi-objective optimization model to formulate the distance of each solution from the positive ideal solution and the negative ideal solution. We develop an ε-dominance multi-objective genetic algorithm to solve the problem of Web service composition optimization. The Pareto frontier, the set of optimal compromise solutions, supports users of either making a flexible decision or choosing an alternative when current service fails. Experimental results verify that the algorithm has satisfying convergence, distribution, and scalability and its computing complexity surpasses the popular non-dominated sorting genetic algorithm (NSGA-II) and strength Pareto evolutionary algorithm 2 (SPEA2).
鲁城华，寇纪淞. 基于多目标多属性决策的大规模Web服务组合QoS优化[J]. 管理学报, 2018, 15(4): 586-.
LU Chenghua，KOU Jisong. Optimization of Large Scale QoS-Oriented Web Service Composition Based on Multi-Objective and Multi-Attribute Decision Making. Chinese Journal of Management, 2018, 15(4): 586-.
