Synchronizing production scheduling with resources allocation for precast components in a multi-agent system environment. (October 2018)

• Record Type: Journal Article
• Authors: Wang, Zhaojing; Hu, Hao; Gong, Jie; Ma, Xiaoping
• Is Part Of: Journal of manufacturing systems. Volume 49(2018)
• Page Start: 131
• Page End: 142
• Publication Date: 2018-10
• Subjects: Production scheduling -- Resource allocation -- Genetic algorithm -- Multi-agent system -- Precast construction; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.09.004
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: The two-hierarchy resource constraints based production scheduling model is proposed The production scheduling and resources allocation are synchronized. Both the flexible and optimized production planning are achieved using the multi-agent system and heuristic algorithms. Abstract: The performance of precast construction is highly dependent on the effectiveness of production planning for the precast components (PCs). However, existing studies focused primarily on the separate mathematical optimization of production scheduling or resource allocations using heuristic algorithms without considering the interactions between each other and the flexible production environment. This paper proposes a multi-agent based precast production planning model to synchronize the production scheduling and resource allocation. In this model, the on-time delivery, minimum waiting and extension time are achieved using a two-hierarchy resource constraints based production scheduling optimization method. Further, the heuristic algorithm is presented to integrate the optimization techniques with the competing goals shown in a multi-agent system. Finally, a real case is conducted to verify the performance of the proposed model. The results demonstrate that 9.1% and 27.4% cost savings can be achieved by comparison to the actual scheduling method in practice and the traditional scheduling methods without considering the resource constraints, respectively. This proposed methodology will support flexible and optimized decision makings on the precast production planning.