4.7 Article

Synchronizing production scheduling with resources allocation for precast components in a multi-agent system environment

Journal

JOURNAL OF MANUFACTURING SYSTEMS
Volume 49, Issue -, Pages 131-142

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2018.09.004

Keywords

Production scheduling; Resource allocation; Genetic algorithm; Multi-agent system; Precast construction

Funding

  1. Key Technology and Development Program in Shanghai of the Shanghai Commission of Science and Technology [14DZ1207101]

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available