A discrete time-cost-environment trade-off problem with multiple projects: the Jinping-II Hydroelectric Station large-scale deeply buried tunnel group project

Innovative contracting methods and stronger environmental protection regulations focused on reducing environmental impact through new incentives have placed increasing pressure on decision makers, especially those on hydroelectric construction projects. This increase has led to a need to identify optimal scheduling and select the most efficient construction modes for each activity to minimise not only the project's time and penalty costs but also its environmental impact. To address this need, this paper applies a mathematical model based on a hybrid genetic algorithm with fuzzy logic controller (flc-hGA) to the discrete time-cost-environment trade-off problem with multiple projects (DTCETP-mP) under a fuzzy environment. Unlike traditional optimisation techniques, which cannot cope effectively with this problem, the optimisation method proposed here is able to extend a single project trade-off analysis to a multiple project trade-off scenario with the practical objectives of minimising total project time, total penalty costs, and the environmental impact of all subprojects. Applying the proposed method to the case study of the Jinping-II Hydropower Station, a large-scale deeply buried tunnel group project in Southwest China, clearly demonstrates its economic, technological, and social ecological effectiveness.