In this paper, we propose a population-based evolutionary multiobjective optimization approach to design combinational circuits. Our results indicate that the proposed approach can significantly reduce the computational effort required by a genetic algorithm (GA) to design circuits at a gate level while generating equivalent or even better solutions (i.e., circuits with a lower number of gates) than a human designer or even other GAs. Several examples taken from the literature are used to evaluate the performance of the proposed approach.

Poor definition and uncertainty are primary characteristics of conceptual design processes. During the initial stages of these generally human-centric activities, little knowledge pertaining to the problem at hand may be available. The degree of problem definition will depend on information available in terms of appropriate variables, constraints, and both quantitative and qualitative objectives. Typically, the problem space develops with information gained in a dynamical process in which design optimization plays a secondary role, following the establishment of a sufficiently well-defined problem domain. This paper concentrates on background human–computer interaction relating to the machine-based generation of high-quality design information that, when presented in an appropriate manner to the designer, supports a better understanding of a problem domain. Knowledge gained from such information combined with the experiential knowledge of the designer can result in a reformulation of the problem, providing increased definition and greater confidence in the machine-based representation. Conceptual design domains related to gas turbine blade cooling systems and a preliminary air frame configuration are introduced. These are utilized to illustrate the integration of interactive evolutionary strategies that support the extraction of optimal design information, its presentation to the designer, and subsequent human-based modification of the design domain based on knowledge gained from the information received. An experimental iterative designer or evolutionary search process resulting in a better understanding of the problem and improved machine-based representation of the design domain is thus established.

Engineer–computer interaction (ECI) is a new subdomain of human–computer interaction that is specifically tailored to engineers' needs. ECI uses an information classification schema, provides a modular approach to task decomposition, and integrates standard engineering characteristics and working procedures into software. A software tool kit that interprets monitoring data taken from bridges was developed according to ECI guidelines. This tool kit was given to engineers for testing and evaluation. An empirical evaluation using questionnaires was performed. The results show that this ECI software corresponds to engineers' needs and the ECI approach has potential applications to other engineering tasks.

In order to respond to the difficulties encountered by CAD software applications in really assisting the conceptual designer, we propose a tool that is capable of interpreting design sketches and feeding data to various project evaluators, right from the early phases in the design process. For that purpose, we use the concept of the absent interface, which is the only interface that is compatible with the cognitive process involved in sketching. In this paper, we present the principles of such an interface, illustrated by EsQUIsE, a software prototype for capturing and interpreting architectural sketches, which has been under development for several years.

Design consists of analyzing scenarios and proposing artifacts, obeying the initial set of requirements that lead from initial to goal state. Finding or creating alternative solutions, analyzing them, and selecting the best one are expected steps in the designer’s decision making process. Very often, not a sole designer, but a team of them is engaged in the design process, sharing their expertise and responsibility to achieve optimum projects. In a design team, most conflicts occur due to misunderstanding of one’s assessment of specifications and contexts. Decision explanations play a key role in teamwork success. Designers are rational agents trained to follow rational methods. Acceptable justifications include value function, requirements, constraints, and criteria. Generally, explanations are delivered in a multimedia fashion, composed of text, graphics and gestures, to provide the audience the ability to perceive what was contextually imagined. The more spatial the reasoning is, the richer the explanation channel should be. This paper presents CineADD, a design explanation generation model based on cinema techniques such as animation, scripting, editing, and camera movements. The idea is to provide designers with a tool for describing the way their projects should be visually explained, as in a movie. Designers develop their projects in an active design document environment. Rationale is captured as a design model, so explanations can be generated instead of retrieved. The captured design model serves as a base to visually reconstruct design, giving emphasis and guidance by using movie storytelling techniques. CineADD was implemented for the domain of oil pipeline layout showing the feasibility of this approach. We expect CineADD to become a commodity attachable to any intelligent CAD system.

The two main ways to search for information in electronic document collections are by using free-text retrieval search engines or browsing information that has been organized into predefined organizational structures. However, each of these approaches has limitations. Using word or phrase search, users are faced with a compromise between overly broad searches returning an excessive amount of information or overly narrow searches that may fail to return relevant information. Browsing organizational structures is dependent on the user's knowledge of the structures, and a user may find it difficult to refine searches. This paper introduces a user interface based approach to the browsing of hierarchically organized information entities that avoids these problems by allowing the incremental narrowing down of a set of search results and by pruning the organizational structure after each user selection to show the consequences of the selection. The effect is to present to the user at all times only that part of the organizational structure that will lead to a nonnull selection. The approach is called no zero match (NZM) browsing. The paper presents the computational basis of NZM browsing before describing a trial implementation of the approach and presenting three case studies, which represent common search situations in an engineering context.