Genetic Algorithm Based optimization of Construction Site Layout of Prefabricated Buildings

Author(s):  
Yizhi Yang
Author(s):  
Panagiotis M. Farmakis ◽  
Athanasios P. Chassiakos

AbstractThe dynamic construction site layout planning (DCSLP) problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time)-hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indicate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process.


Author(s):  
Pham Vu Hong Son

The efficient plan of site arrangement during the construction phase has been considered a vital duty to successful project performance due to the productivity enhancement as well as safety in executions. The optimization of the Construction Site Layout Problem (CSLP) is a combinatorial complexity that regards numerous objectives and considerable growth of scale as increasing of constraints and facilities. The rearrangement on site may thus need to be had dynamic plannings at several interval schedules as construction evolves to accommodate site needs. To resolve the complexity of this problem, many studies based on the Meta-heuristic approach have been done, there are however always drawbacks and should be improved to be more optimal. This research proposes a new Hybrid Meta-heuristic model which is a combination of Ant Colony Optimization algorithm (ACO), Bacterial foraging algorithm (BFA), and Pair-Wise Exchange Heuristic algorithm (PWEH). The proposed algorithm is named Dynamic Hybrid Ant Colony Algorithm (DHACA) model that can enhance local and global searches simultaneously. In addition, parameter values are optimized to create a better solution. This research also demonstrates the effectiveness of DHACA compared with the previous studies such as Multi-objectives Genetic Algorithm (MOGA), Simulated Annealing Algorithm based Multi-objectives Genetic Algorithm (SA-based MOGA) on the CSLP. DHACA supports the construction site dynamic planning with constraints on facilities to improve work efficiency.  


2002 ◽  
Vol 11 (5) ◽  
pp. 511-519 ◽  
Author(s):  
J.P. Zhang ◽  
L.H. Liu ◽  
R.J. Coble

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