Document Type : Research Paper

Authors

• Ali Namazian ¹
• Somayeh Behboodian ²

¹ Assistant professor, Department of Industrial Engineering, College of Engineering, University of Kashan, Kashan, Iran

² Master's student in Industrial Engineering, Faculty of Engineering, Isfahan University, Isfahan, Iran

Abstract

Projects, during their execution, face various risks that can impact the achievement of project objectives. Therefore, the need for extensive project risk management is widely recognized. In a systematic risk management process, after risk evaluation, risk analysts are confronted with the risk response phase, where they decide on the actions to be taken regarding identified risks. Hence, designing and implementing a structured approach to manage and mitigate risks will yield beneficial outcomes for successful completion within the desired budget, time, and quality. In conducted studies, a comprehensive approach that integrates the time and cost implications of risks and response strategies has been lacking. In this article, an optimization model of zero-one programming has been employed to select the most suitable risk response strategies for the project. In the developed framework, the modeling of the impact of risks on the time and cost of activities, as well as the effect of implementing risk response strategies on reducing the undesirable time and cost implications of risks, has been utilized to select optimal strategies. Finally, to evaluate the efficiency of the model, an industrial case study was utilized, which confirmed the favorable performance of this framework.
Introduction
Every project throughout its lifespan faces opportunities and risks. Risks are uncertain outcomes or consequences of activities or decisions. Therefore, in the project planning process, it is necessary to identify potential risks and then consider appropriate strategies to deal with various risks. In this article, a mathematical programming model is used to evaluate and analyze project risks and to select project risk responses. This model considers the probabilistic nature of risk events and develops an index for evaluating the time and cost impacts of risks, as well as response strategies. The proposed approach can be used to select the best combination of risk response strategies that have the most impact on the time and cost of implementing activities, resulting in completing the project with minimum time and cost.
Literature Review
Different models have been developed for project risk management to enhance success in development projects. These approaches utilize various structures and tools to quantitatively or qualitatively model the selection of risk response strategies for the project. In recent years, due to unexpected events such as financial crises, significant delays have occurred in projects worldwide (Motaleb, 2021). Thus, researchers have attempted to propose various methods to mitigate the effects of risks in recent years.
In the Zonal-based approach, two selected criteria based on risks are plotted on the horizontal and vertical axes, respectively. The two chosen criteria are the weighted probability of immediate project risk and external project risk, and the controllability and specificity of the risks related to the project. Based on the different values of these two criteria, a two-dimensional chart consisting of multiple regions is formed. Different strategies are placed in the corresponding regions. Therefore, suitable strategies can be selected based on the regions formed by the coordinates of the two criterion values.
In the Trade-off-based approach, in order to identify the selected risk for formulating response strategies, exchanges are conducted considering the project's goals, requirements, and managers' mental settings among risk-related criteria such as cost, success probability, percentage of work losses, duration, quality, etc. Then, desirable strategies can be selected from the options based on the efficiency frontier rule.
The approach based on WBS is considered a risk management and project management method. This choice aligns the risk response strategy with the work activities based on WBS analysis of the project. (Guan et al., 2023) developed an integrated approach based on an optimization model and fault tree analysis for budget allocation in response to risk from safety and prevention perspectives.
The optimization approach involves creating a mathematical model to solve the problem of selecting risk response strategies. In general, the objective function aims to minimize the cost of implementing strategies, and the constraints include combinations of strategies, an acceptable level of risk loss, budget for implementing strategies, etc.
Methodology
In this study, a set of work activities is considered, and for each work activity, there may be associated risks that can have an impact. Then, risk response strategies are modeled to determine the most desirable strategy. The zero-one programming technique is used to solve the model. By solving the model, strategies are selected that maximize the estimated impact of risk response after implementation and minimize the cost of implementation. In the proposed model, a set of actions is selected in a way that satisfies the system constraints and optimizes the corresponding objective function. The objective function can be related to time or cost, and the goal of the model is to minimize project completion time or project cost. The model constraints are related to time and cost. The time constraint means that selected strategies should not exceed the specified time frame for their execution and impact on time. The cost constraint means that selected strategies should not exceed the budget and predefined cost in terms of their cost and impact on cost.
 Results
The model presented in this study has an objective function and nine constraints. The purpose of this model is to determine strategies that minimize project completion delay and help achieve and improve project goals. Due to the structure of the modeling, including the objective function and problem constraints, the complexity of the model will change polynomially based on the number of risks, response strategies, and project activities. If simulation-based approaches are used to solve the model, considering the binary nature of project risks and replacing it with the expected value, the complexity of the solution approach will be exponential. Therefore, using the logic of expected value to calculate the duration of activities and project completion time will accelerate the solution process.
Discussion and conclusions
In a systematic project risk management process, after assessing the risks, the implementation of project risk response strategies takes place. The conducted research has generally provided general solutions, and there is no comprehensive model for evaluating project risk reduction measures. In this article, a mathematical optimization model has been developed by considering the risks and response strategies as independent variables for each work activity. Essentially, based on the potential risks that may occur for each work activity, strategies are chosen to minimize project completion delay and reduce the incurred costs, ultimately achieving the project's completion with the least delay and cost. Implementing risk response strategies to mitigate the time and cost impacts of risks requires time and investment. Therefore, selecting these strategies will be justifiable when the time and cost benefits derived from their implementation are greater than the time and cost spent.

Keywords

• Risk Event
• Risk Assessment
• Risk Response Strategy
• Optimization Model
• Time and Cost Impact

Main Subjects

• project management