The outbreak of the novel coronavirus COVID-19 has caused enormous impacts on various social, economic, and health spectrums. Rapid decline in the mobility trends have been detected with the declaration of the stay-at-home order on March 21 in New Jersey (NJ), upon which non-essential workers started operating remotely. The traffic pattern started shifting with the lift of the stay-at-home order on June 9. While maintenance projects are deemed essential in NJ, transportation agencies are investigating ways to work in a safe environment, yet finish their maintenance projects on time for the reopening stage. This paper investigates the effect of traffic demand variations during COVID-19 lockdown on work zone optimization using the Artificial Bee Colony algorithm. A case study was conducted to evaluate the optimized schedules in three different phases. The first phase depicts the normal traffic conditions, the second phase reflects the lockdown conditions due to the declaration of the stay-at-home order, and the third outlines the traffic conditions after lifting the order. INRIX data is used to estimate the decrease in traffic volumes during those phases. The results indicate that work zone optimization during COVID-19 lockdown period may significantly reduce the project duration while saving on the project total cost. In addition, the crew assigned during lockdown period may consist of few workers, which allows social distancing measures. The findings of this study can assist transportation agencies with managing the work zone optimization scheduling problem during current and any future lockdown conditions.