Constructing a Multi-Objective Optimization Model for Engineering Projects Based on NSGA-II Algorithm under the Background of Green Construction

Abstract

In the context of Sustainability Development (SD), Green Construction (GC) has become a key direction for optimizing engineering project objectives. In order to improve the management ability of project engineering in GC, an improved NSGA - II algorithm was used in this study to establish a multi-optimization model for engineering projects. In this process, the hill climbing is introduced to improve the search ability of NSGA - Ⅱ algorithm. Finally, a Multi-Objective Optimization (MOP) model with strong convergence and distribution was obtained. In subsequent validation experiments, the total construction period of the engineering project MOP model based on the improved NSGA - II algorithm was between 190 and 234days. The total cost ranges from 171,473 to 20,461,800 yuan. Its total mass ranges from 90.41% to 92.19%. Its total safety is between 91.30% and 99.32%. The total environment is between 144.54 and 193.58. Its total resources range from 86.21% to 99.91%. The cost of improving the NSGA-II algorithm is 500300 yuan lower than that of the NSGA-II algorithm, with a resource target increase of 0.4% and an environmental target increase of 4.33%. The iteration curves of the improved NSGA - II algorithm in terms of duration, cost, and environmental objective function are lower than those of the NSGA - II algorithm. Overall, the improved NSGA - II algorithm has better MOP performance, can obtain better Pareto solutions, and has better performance.

Finance-based Scheduling for Cash-flow Management of Maintenance Portfolios: Multi-objective Optimization Approach

“…In a survey conducted on the use of multi-objective algorithms in construction project management during the period 2012-2016, Alothaimeen and Arditi [47] reported that NSGA-II was the most commonly used algorithm. Recent applications of NSGA-II in project management included sustainability development, green construction, and carbon emissions as optimization objectives [48,49]. In NSGA-II, fitness is assigned according to a two-level criteria, the first depends on the dominance rank of the individuals, whereas the second is assigned considering the crowding distance of the individuals of the same dominance rank.…”