BUS606: Operations and Supply Chain Management

Various risks and uncertainties exist in EPC projects. They lead to projects not completed within time and cost limits. In the construction industry, contractors always use previous execution experiences to estimate project durations and costs, which lead to many risks during project execution. This study presents the frameworks of project schedule risk analysis and time-cost trade-off strategy. It introduces a hybrid method for solving time-cost trade-off problems based on Monte Carlo simulation and integer linear programming. Monte Carlo simulation is initially used to develop the probability distribution of the possible project completion duration in different scenarios by considering potential risks, and integer linear programming is applied to determine the crashing strategy for time-cost optimization.

Monte Carlo simulation can be used for the engineering schedule risk analysis to obtain the most probable project completion time by identification of risk factors and sensitivity analysis. Qualitative and quantitative risk analyses should be conducted for all potential risk items during the quotation phase. As in the case study, the project completion duration specified in the contract, which is 976 days, turns out to be an impossible requirement because the simulation results validate that the total project duration is 1,079 days with 80% probability and 1,123 days with 100% probability after considering the risk mitigation effects. On the basis of the risk analysis result, a contractor might propose a reasonable schedule to the owner to avoid the fine caused by schedule delay. But the owner would not accept it and would disqualify the contractor from the bidding. On the other hand, paying delay penalties will result in serious damage to the corporation's reputation, so companies are not inclined to choose this option. Therefore, contractors must determine crashing strategies and assess whether to approach this project. This study introduces a new hybrid method to provide a simple tool to evaluate project execution under a crashing strategy and risk consideration. The proposed hybrid method selects the most critical path using a schedule sensitivity index from Monte Carlo simulation results and then uses a mathematical integer linear programming optimization method to solve the constructed model for the selected path. This model can be effectively applied in a practical EPC project for assessment during a bidding stage and may help project planners to manage the project completion time accurately from a risky amount to a desirable predefined value. This approach will also allow managers to understand the trade-off between project execution time and cost under crashing strategies and risk consideration. It enables managers to optimize their decision-making reference while approaching a project.

This study provides comprehensive plans for project schedule risk analysis and time-cost trade-off strategy, identifies and understands the critical path and near critical paths through a real case study, proposes a hybrid approach with Monte Carlo simulation and mathematical integer linear programming to solve problems related to project scheduling, constructs a mathematical model of the project crashing strategy coded by CPLEX to determine the optimal project completion schedule and minimize the total cost, analyzes the relationship between project crash cost and delay penalty, and provides reference points to project budgeting under crashing strategy and risk consideration.