This session will focus on Real-Option Valuation (ROV) methodologies and applications to optimal decision-making in a highly uncertain environment. The ROV framework for quantifying the value of decisions under uncertainty has originated from the financial options pricing theory. The approach is multidisciplinary in nature, integrating financial option pricing theory with operation research to form a special field of decision sciences. ROV can be applied to a wide range of strategic and operating decision processes, such as procurement strategies in defence and infrastructure, optimal decisions in agriculture and environmental impact management, operating decisions and life-cycle management in minerals and manufacturing industries. ROV methodologies have advanced substantially: stochastic dynamic programming techniques and latest analytical tools from computational finance (such as advanced Monte Carlo and Least Square Monte Carlo approaches) are currently adopted. The session will provide the opportunity for practitioners and academic researchers to exchange ideas and present their experiences in applying ROV to business decision-making under future uncertainty in industries such as asset management, infrastructure, defence, agriculture, mining, aid development and others.