An enhanced multi-objective optimization approach for risk allocation in public–private partnership projects: a case study of Malaysia

Abstract

The decision making for risk allocation problems in public–private partnership (PPP) projects is a vital process that directly affects the timeliness, cost, and quality of the project. Fair risk allocation is a vital factor to achieve success in the implementation of these projects. It is essential for private and public sectors to apply efficient risk allocation approaches to experience a more effective process of agreement arbitration and to reduce the appearance of dispute during the concession period. The aim of this study is to develop an optimization approach to enhance risk allocation process in PPP projects. The shared risks in projects are identified through comprehensive literature review and questionnaire survey obtained from Malaysian professionals involved in PPP projects. Objective functions are then developed to minimize the total time and cost of the project and maximize the quality while satisfying risk threshold constraints. The combinatorial nature of the risk allocation problem describes a multi-objective situation that can be simulated as a knapsack problem (KP). The formulation of the KP is described and solved applying genetic algorithm (GA). Due to the flexibility of GA, the results are Pareto Optimal solutions that describe the combinations of risk percentages for shared risks in PPP projects.