The conceptual design phase is the most critical phase in the systems engineering life cycle. The design concept chosen during this phase determines the structure and behavior of the system, and consequently, its ability to fulfill its intended function. A good conceptual design is the first step in the development of a successful artifact. However, decision-making during conceptual design is inherently challenging and often unreliable. The conceptual design phase is marked by an ambiguous and imprecise set of requirements, and ill-defined system boundaries. A lack of usable data for design evaluation makes the problem worse. In order to assess a system accurately, it is necessary to capture the relationships between its physical attributes and the stakeholders\u27 value objectives. This research presents a novel conceptual architecture evaluation approach that utilizes attribute-value networks, designated as \u27Architecture Value Maps\u27, to replicate the decision makers\u27 cogitative processes. Ambiguity in the system\u27s overall objectives is reduced hierarchically to reveal a network of criteria that range from the abstract value measures to the design-specific performance measures. A symbolic representation scheme, the 2-Tuple Linguistic Representation is used to integrate different types of information into a common computational format, and Fuzzy Cognitive Maps are utilized as the reasoning engine to quantitatively evaluate potential design concepts. A Linguistic Ordered Weighted Average aggregation operator is used to rank the final alternatives based on the decision makers\u27 risk preferences. The proposed methodology provides systems architects with the capability to exploit the interrelationships between a system\u27s design attributes and the value that stakeholders associate with these attributes, in order to design robust, flexible, and affordable systems --Abstract, page iii
