Optimal earthmoving-equipment combination considering carbon emissions with an indicator-based multiobjective optimizer

Reasonable earthmoving-equipment combinations have helped to reduce duration and cost in the construction industry traditionally. However, reducing carbon emissions in earthmoving operations is highly desirable because earthmoving operations involve a large number of heavy equipment, which produce high carbon emissions. It is necessary to study a novel equipment combination optimization model considering decreasing carbon emissions in addition to duration and cost. Hence, a triobjective equipment combination optimization (ECO) model is developed, minimizing carbon emissions as well as project duration and cost. In this model, the excavation and transportation processes of earthwork are regarded as a queuing system, and queuing theory is integrated directly into the model to compute the involved parameters instead of a simulation. On the other hand, for obtaining the optimal solution set of the multiobjective problems with more objectives, a novel two-archive multiobjective particle swarm algorithm is proposed, which updates individuals in archives by not only Pareto domination but also an indicator that can assess solution quality. A real case study demonstrated that the model can efficiently provide a reasonable earthmoving-equipment combination considering the trade-off among carbon emissions, duration, and cost for managers.