Abstract
It is extensively acknowledged that excessive on‐site electricity power load often causes power failure across a construction site and surrounding residential zones and can result in unforeseen schedule delay, construction quality problems, life inconvenience, and even property loss. However, energy management, such as power load optimization, has long been ignored in construction scheduling. This study aims to develop a modified shuffled frog‐leaping algorithm (SFLA) approach in project scheduling to aid decision‐makers in identifying the best Pareto solution for time‐cost‐resource trade‐off (TCRTO) problems under the constraint of precedence, resource availability, and on‐site peak electricity power load. A mathematical model including three objective functions and five constraints was established followed by the application of the modified SLFA on real‐case multiobjective optimization problems in construction scheduling. The performance of SLFA was compared with that of the nondominated sorting genetic algorithm (NSGA II). The results showed that the developed new approach was superior in identifying optimal project planning solutions, which could essentially assist on‐site power load‐oriented schedule decision‐making for construction teams.
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