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Cox, R F, Issa, R R A and Koblegard, K (2005) Management’s Perception of Key Behavioral Indicators for Construction. Journal of Construction Engineering and Management, 131(03), 368–76.

Gunhan, S and Arditi, D (2005) Factors Affecting International Construction. Journal of Construction Engineering and Management, 131(03), 273–82.

Han, S H, Diekmann, J E and Ock, J H (2005) Contractor’s Risk Attitudes in the Selection of International Construction Projects. Journal of Construction Engineering and Management, 131(03), 283–92.

Jaselskis, E J, Gao, Z and Walters, R C (2005) Improving Transportation Projects Using Laser Scanning. Journal of Construction Engineering and Management, 131(03), 377–84.

Kim, K and de la Garza, J M (2005) Critical Path Method with Multiple Calendars. Journal of Construction Engineering and Management, 131(03), 330–42.

Lee, D (2005) Probability of Project Completion Using Stochastic Project Scheduling Simulation. Journal of Construction Engineering and Management, 131(03), 310–8.

  • Type: Journal Article
  • Keywords: Critical path method; Monte Carlo method; Probability; Risk analysis; Scheduling; Simulation; Stochastic models;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:3(310)
  • Abstract:
    This paper introduces a software, Stochastic Project Scheduling Simulation (SPSS), developed to measure the probability to complete a project in a certain time specified by the user. To deliver a project by a completion date committed to in a contract, a number of activities need to be carried out. The time that an entire project takes to complete and the activities that determine total project duration are always questionable because of the randomness and stochastic nature of the activities’ durations. Predicting a project completion probability is valuable, particularly at the time of bidding. The SPSS finds the longest path in a network and runs the network a number of times specified by the user and calculates the stochastic probability to complete the project in the specified time. The SPSS can be used by a contractor: (1) to predict the probability to deliver the project in a given time frame and (2) to assess its capabilities to meet the contractual requirement before bidding. The SPSS can also be used by a construction owner to quantify and analyze the risks involved in the schedule. The benefits of the tool to researchers are: (1) to solve program evaluation and review technique problems; (2) to complement Monte Carlo simulation by applying the concept of project network modeling and scheduling with probabilistic and stochastic activities via a web based Java Simulation which is operateable over the Internet, and (3) to open a way to compare a project network having different distribution functions.

Molenaar, K R (2005) Programmatic Cost Risk Analysis for Highway Megaprojects. Journal of Construction Engineering and Management, 131(03), 343–53.

Moselhi, O, Assem, I and El-Rayes, K (2005) Change Orders Impact on Labor Productivity. Journal of Construction Engineering and Management, 131(03), 354–9.

Rojas, E M and Mukherjee, A (2005) General-Purpose Situational Simulation Environment for Construction Education. Journal of Construction Engineering and Management, 131(03), 319–29.

Shapira, A and Raz, Y (2005) Comparative Analysis of Shoring Towers for High-Clearance Construction. Journal of Construction Engineering and Management, 131(03), 293–301.

Son, J, Mattila, K G and Myers, D S (2005) Determination of Haul Distance and Direction in Mass Excavation. Journal of Construction Engineering and Management, 131(03), 302–9.

Song, L and AbouRizk, S M (2005) Quantifying Engineering Project Scope for Productivity Modeling. Journal of Construction Engineering and Management, 131(03), 360–7.