Service requirement conflict resolution based on ant colony optimization in group-enterprises-oriented cloud manufacturing

• Published in: International journal of advanced manufacturing technology Vol. 84; no. 1-4; pp. 183 - 196
• Main Authors: Huang, Xiaorong, Du, Baigang, Sun, Libo, Chen, Feng, Dai, Wei
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2016; Springer Nature B.V
• Subjects: Algorithms; Ant colony optimization; CAE) and Design; Computer-Aided Engineering (CAD; Conflict resolution; Engineering; Industrial and Production Engineering; Manufacturing; Mathematical models; Mechanical Engineering; Media Management; Original Article; Schedules; Task scheduling; Group enterprises (GE); Serial schedule generation scheme (SSGS); Cloud manufacturing (CMfg); Conflict resolution; Ant colony optimization (ACO)
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-015-7961-x

Cloud manufacturing (CMfg) platform for group enterprises (GE) is a kind of private CMfg, which is to integrate and optimize GE’s internal resources and capacity for large complex equipment manufacturing. The platform makes a connection between distributed and heterogeneous manufacturing resources to build a virtual pooling of resources for the group. However, it is evident that uncertainties and dynamics inherently exist in the platform and it causes manufacturing service requirement conflict among multiple projects. In order to address this issue, the management process of large complex equipment manufacturing project in GE-oriented CMfg platform is described. And next, this paper analyzes the causes and characteristic of service conflict in the platform. Then, a multi-objective mathematical model of conflict resolution is proposed. The proposed model considered both global target of shortest duration and partial target of tasks change minimization. Moreover, a method based on serial schedule generation scheme (SSGS) and ant colony optimization (ACO) algorithm is put forward to solve the model. Finally, a conflict resolution case study in a cement equipment manufacturing group enterprise is provided to illustrate the application of the proposed the model and algorithm.