Optimal Earthmoving-Equipment Combination Considering Carbon Emissions with an Indicator-Based Multiobjective Optimizer

Abstract

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. A multiobjective model for obtaining the optimal earthmoving-equipment combination is proposed in this paper. In addition to traditional reductions in duration and cost, the model also considers sustainability requirements by reducing carbon emissions in the construction industry. In other words, this model can offer the solutions of equipment combinations in terms of not only reducing the cost and duration to construction managers, but also reducing carbon emissions. Instead of one combination of earthmoving equipment, a set of nondominated solutions is offered in this model, and this allows managers to make choices based on specific site conditions. In addition, the authors have improved the traditional algorithm to obtain the solutions to better meet the needs of users. This new earthmoving-equipment combination optimization model can quickly get reasonable equipment combinations and helps minimize carbon emissions as well as duration and cost. This model has been applied to a real earthwork project in China and gave the optimal excavator-truck configuration that satisfied the contractor.