This session will focus on Real Options Analysis (ROA) methodologies and applications to flexible project management and valuation, and optimal decision-making in a highly uncertain environment. The ROA framework has originated from financial options pricing theory and is based on the concept that the flexibility to revise managerial and/or operational decisions over time in response to resolution of uncertainty can significantly increase project value. The approach is multi-disciplinary in nature, integrating financial option pricing theory with stochastic optimal control to form a special field of decision science. ROA can be applied to a wide range of industrial problems of optimal project planning and management and decision making under uncertainty, e.g. in minerals and manufacturing industries, agriculture and environmental impact management. ROA methodologies have advanced substantially over the past decade: the latest analytical tools from computational finance and stochastic optimal control are currently being adopted. The regression-based Monte Carlo methods (such as the least-squares Monte Carlo) are among the most promising techniques for high-dimensional real life industrial problems. The session will provide the opportunity for practitioners and academic researchers to exchange ideas on new methods and algorithms for ROA and to present their experiences in applying ROA to business decision making under uncertainty in industries such as mining, asset management, infrastructure, energy, defence, agriculture and aid-development.