Risk management and control of project risks have been the intrinsic characteristics of high-rise oil and gas projects in a changing of engineer-procure-construct (EPC) projects. In this research, a novel bi-objective optimization model for the best mixture of projects is proposed. The first objective focuses on maximizing profits and efficiency of risk responses, and the second objective aims at minimizing project direct cost including machinery, human, and material costs to implement proper risk responses over a planning horizon under uncertainty. In this model, risks of the projects are controlled by time, quality, and cost constraints, and the most optimum risk response strategies (RRSs) are selected to eliminate or reduce the impacts of the risks. Thus, the combination of optimum projects with the best RRSs can be selected for an organizational portfolio model. As this model is complex and difficult to solve, another novelty of this paper is to propose a novel hybrid metaheuristic as a combination of red deer algorithm (RDA) and particle swarm optimization (PSO) to address the proposed optimization model. Multi-objective assessment metrics are also employed to have a comparison among this hybrid metaheuristic and its individual ones. Finally, to assess the proposed solution method and the developed model, the empirical result and sensitivity analysis are carried out. Some large-scale high-rise EPC projects and their associated risks are evaluated as our test cases in this study and managerial insights are concluded from the results.
