Abstract
Reasonable production scheduling plays a vital role in the production of precast component factories. However, previous static scheduling models no longer fit actual production. In particular, some factors will cause errors in the actual delivery time of the components, including the lack or redundancy of processes in the model, resource constraints required by the core processes, and differences in transportation schemes. Moreover, the optimization goal of simply pursuing the minimization of fines from order delivery underestimates companies’ emphases on reputation. Therefore, this study proposes an improved model for precast component production scheduling considering resource constraints. The number of production processes is adjusted to eight, and three resource constraints for mold, steel, and concrete are added. An enterprise decision-making coefficient is introduced into the optimization object function, and the constraints of the transportation scheme are improved. Finally, a real case study is conducted to verify the applicability of the model. Compared with previous models, the developed model fills the gap in considering production resource constraints and enterprise decisions in precast production, can better meet diverse production conditions and business needs of factories for scheduling, and help give full play to the advantages of prefabricated construction.
Highlights
A prefabricated building refers to a building constructed by transferring a large amount of the on-site work of traditional construction to a factory, transporting the building components processed in the factory to the construction site, and assembling them on site
The genetic algorithm is utilized as the engine to select the optimal processing order of the precast components according to the optimization objective. This proposed model fills the gap in considering production resource constraints and enterprise decisions in precast production, which will enhance the accuracy of scheduling, enrich the application scenarios of production, and promote the development of prefabricated construction
To solve the above problems, this study introduces an enterprise decision-making coefficient into the optimization objective function; that is, the optimization objective function can be adjusted by changing the value of the coefficient, so that the precast component factory can make flexible decisions based on its own needs in terms of economic and reputation benefits
Summary
A prefabricated building refers to a building constructed by transferring a large amount of the on-site work of traditional construction to a factory, transporting the building components processed in the factory to the construction site, and assembling them on site. Ignoring the above problems will lead to calculation errors in the production completion time and within the narrow application range of the model, affecting the science, accuracy, and practicability of the scheduling model To eliminate these shortcomings, an improved eight-process model of precast component production scheduling considering resource constraints is proposed in this paper. The genetic algorithm is utilized as the engine to select the optimal processing order of the precast components according to the optimization objective This proposed model fills the gap in considering production resource constraints and enterprise decisions in precast production, which will enhance the accuracy of scheduling, enrich the application scenarios of production, and promote the development of prefabricated construction.
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