Optimal Reduction of Project Risk Severity: A Case Study

摘要

Although many studies were carried out to identify the range of risky events in construction projects and the recommended response and precautionary strategies, little has addressed the means of making such decisions in an optimal way. Unfortunately, complex projects are marred with numerous interconnected causes and effects, which make project dynamics rather difficult to understand and control. A research was undertaken to optimize risk treatment in construction projects, where costs and benefits are balanced out at the project level. Study employs ant colony optimization (ACO) and dynamic risk maps (DRM) to achieve the sought research goal. This paper focuses on presenting the mechanics of the research approach via a real life case study. The construction project into consideration was executed by a well-known contractor in the Middle East. The paper first describes the case details. After the identification of project risk events, the risk inter-dependencies were modelled using a DRM, which made use of the professional knowledge of industry professionals and archived project records as well. Furthermore, ACO is utilized for the balanced selection of risk treatment strategies and to help reduce the project's overall risk severity at the minimum cost possible. Paper ends with useful insights into the research approach and outcomes of case study application.