ABSTRACT

As an emerging sharing and collaborative paradigm, the cloud manufacturing system should maximize the satisfaction of stakeholders to promote the long-term development of the system. This article proposes a new utility-aware cloud manufacturing multi-task scheduling model, which considers the utilities of both customers and manufacturers. To solve the proposed model, an extended non-dominated sorting genetic algorithm-II with three improvements is presented to find the approximate optimal Pareto solution set. Then, these non-dominated solutions are ranked by means of game theory, and the resulting optimal solution is recommended to the cloud manufacturing system. Simulation experiments are conducted to verify the effectiveness of the proposed algorithm by comparing it with three baseline multi-objective evolutionary algorithms.

摘要

作为新兴的共享和协作范例，云制造系统应使利益相关者的满意度最大化，以促进系统的长期发展。本文提出了一种新的可感知效用的云制造多任务调度模型，该模型考虑了客户和制造商的效用。为了解决该模型，提出了一种具有三项改进的扩展非支配排序遗传算法-II，以找到近似的最优帕累托解集。然后，利用博弈论对这些非支配的解决方案进行排名，并将得到的最优解决方案推荐给云制造系统。通过与三种基线多目标进化算法进行比较，进行了仿真实验，以验证该算法的有效性。