A construction project scheduling methodology considering COVID-19 pandemic measures

Abstract

Introduction: At the beginning of the COVID-19 pandemic, various social measures were taken and various sectors were affected with strict precautions and safety measurements. The construction industry, where numerous employees work together, was affected by these COVID restrictions. The pandemic period typically further delayed the construction contracts.

Methods: This study addresses the project duration, pandemic risk, and project cost of a construction project case by using both multi-objective genetic algorithm and resource constrained project scheduling techniques, using modeling of COVID-19 infection rate. Finally, the analytic hierarchy process (AHP), a multi-objective technique, is used to obtain an optimal solution using three criteria: project duration, total cost, and pandemic risk value.

Results: A case study is used for analyzing the outcomes of the pandemic-based modeling, the original schedule of the case study ends in 46 days. Feasible schedules are obtained with durations occurring between 61 to 199 days, the pandemic risks range from 46% to 89%, and the total cost varies from 174,669.8 Turkish Lira (TL) to 186,126.7 TL. Consequently, the most optimal-final solution is obtained Alternative 5 (0.46% pandemic risk, 199 Day (10 workers) with 185,722 TL).

Conclusion: We conclude that the possible rate of pandemic-related delays can be obtained by using both these techniques and the infection modeling method. Using the COVID-19 infection rate modeling, duration and cost changes are calculated by considering infection risk in construction workers. Practical Applications: Using the COVID-19 infection rate modeling, project delays and cost overruns are determined by considering infection risk in construction workers. Optimum worker sizes and delayed construction activities are determined according to the selected solution by using the AHP technique. Expectedly, this study may help determine the construction process while preserving social distances between construction workers during pandemic situations like COVID-19.

Keywords: AHP; COVID-19; Multi-objective optimization; OHS; Pandemic.

Fig. 1

Random worker locations with different social distances.

Fig. 2

The upper limit of worker numbers with changing of social distances.

Fig. 3

Average social distance values depending on the worker number.

Fig. 4

The first parallel scheduling steps for a sample network (Source:Klein, 1999).

Fig. 5

A sample Pareto Front for Two Objectives.

Fig. 6

Flowchart of a Generic Multi-Objective GA.

Fig. 7

Pareto results of different labor limits.

Fig. 8

Comparison of four worker condition’s Pareto Front projections.