Abstract
This paper presents a computational method called Stochastic Multi-variate Performance Trade-off (SMPT), which identifies optimal sets of construction methods for activities, hence appropriately trading-off the project completion time, cost, environmental impact, and quality. SMPT computes exact solution(s), near-optimal solution(s), and stochastic optimal solution(s) using an enumerative analysis, genetic algorithm, and simulation, respectively. This study is of value to project planners because SMPT identifies the sets of construction methods that satisfy user-defined constraints relative to specific performance indicators. SMPT is also of relevance to researchers because it facilitates experiments using different performance indicators, either jointly or independently. Three test cases verify the validity of the computational methods.
Original language | English |
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Pages (from-to) | 4240-4253 |
Number of pages | 14 |
Journal | KSCE Journal of Civil Engineering |
Volume | 22 |
Issue number | 11 |
DOIs | |
State | Published - 1 Nov 2018 |
Keywords
- analytic hierarchical process
- genetic algorithm
- multi-objective optimization
- scheduling
- simulation
- trade-off