This dissertation provides a complex adaptive system approach to propose effective problem definitions for problems that are hard to formulate, include conflicting opinions of stakeholders, and have hard to differentiate symptoms from the causes, that is, wicked problems. The traditional problem solving methods do not fully address the issues of the ambiguity and uncertainty associated with a wicked problem. The lack of clarity exposes wicked problems to perceptual biases resulting multiple mental models. These inherent characteristics of wicked problems require methods that are solely focused on identifying, defining, and evaluating discrepancies in perceptions. This dissertation proposes a framework, Quandary Translation Engineering, to address the unique challenges of defining a wicked problem. The framework, inspired from complex adaptive systems, utilizes the engineering method approach. The framework defines problem space as a way to capture the complexity of the wicked problem and creates an incremental and evolutionary model of the wicked problem. Next, the framework generates multiple possible problem definitions from the problem space. Finally, the framework provides measures for evaluating and selecting potential problem definitions from the pool of possible problem definitions. The framework is shown to be effective in defining, evaluating, and selecting problem definitions for wicked problems without relying on the completeness of data and any information about solutions. It was found that framework facilitates managers, decision makers, and analysts in modeling incomplete, vague, and conflicting information regarding a wicked problem. The proposed framework is applied to a Kansas strategic planning exercise for businesses in Kansas.