A Multi Objective Scheduling Model for Minimization of Construction Project Duration, Total Cost and Environmental Impact

The performance of construction projects has traditionally been measured based on cost, time, and quality. Recently, the environment impact has been introduced as a fourth criterion for the assessment of project performance. Significant research advancements have been made in the area of optimizing resource utilization to minimize the total cost, duration, and quality for construction projects. A number of models have been developed using a variety of methods, including heuristics methods, mathematical programming, genetic algorithms, ant colony, and particle swarm optimization. However, there has been little or no reported research focusing on studying and optimizing the collective impact of resource utilization decisions on construction cost, duration, and environmental impact. The objective of this paper is to present the development of a multi-objective optimization model for optimizing resource utilization and scheduling of projects. The model provides construction planners and decision makers with new and important capabilities, including: (1) evaluating the combined impact of multiple resource utilization decisions on construction cost, duration, and environmental impact and (2) generating and visualizing optimal/near-optimal resource utilization and scheduling plans that provide optimal trade-offs between the project cost, duration, and environmental impact. The model is developed in two stages: (1) model formulation to identify the decision variables and optimization objectives for the construction optimization problem and (2) model implementation to perform the optimization computations using three modules that compute project duration, total cost, and environmental impact, respectively. © 2019 The Authors. Published by Budapest University of Technology and Economics & Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2019.