Topology deals with geometric properties that are dependent only on the relative positions of the components of figures and not on such concepts as length, size, and magnitude. Topology supports design and representation of mechanical devices, communication and transportation networks, topographic maps, and planning and controlling of complex activities. In addition, aspects of topology are closely related to symbolic logic, which forms the foundation of artificial intelligence. By approaching engineering design from this abstract point of view, it is possible to use topological methods to study collections of geometric objects or collections of entities that are of concern in design analysis or synthesis. The importance of topological representation and reasoning in analysis, design, and manufacturing is heightened by the contemporary view that stresses the need for conceptual design.

Collaborative engineering design involves various stakeholders with different perspectives. The design process is relatively complex and difficult to handle. Various conflicts always happen among the design tasks and affect the design team performance. Therefore, to represent the collaborative design process and capture the evolution of design perspectives in a structured way, it is critical to manage the design conflicts and improve the collaborative design productivity. This article provides a generic collaborative design process model based on a sociotechnical design framework. This model has a topological format and adopts process analysis techniques from Petri Nets. By addressing both the technical and social aspects of collaborative design activities, it provides a mechanism to identify the interdependencies among design tasks and perspectives of different stakeholders. Based on this design process model, a methodology of detecting and handling the design conflicts is developed to support collaborative design coordination.

When the idea of software reuse appeared in 1968, new horizons for software design were open. But some major problems appeared and most of the expectations were not met. One of the problems encountered is the selection of the right software component. This is related not only to the similarity between the desired functionality and the function delivered by the retrieved software component, but also to the effort needed to modify the chosen component to accommodate the desired functionality. Most of the research done in the case-based reasoning area has been in developing accurate and efficient retrieval algorithms. We think that case-based reasoning retrieval concepts and ideas can be successfully applied to software reuse. In this article we propose a metric to assess similarity between software cases supported on functional and behavioral knowledge. One important aspect of this metric is that reusability is taken into account to estimate the amount of effort needed to reuse retrieved software cases. We also present experimental work that shows that similarity at the functional level is the most important aspect of the similarity metric proposed.

The problem of finding optimal values in complex parameter optimization problems has often been solved with success by evolutionary algorithms (EAs). In many cases, these algorithms are employed as black-box methods over imprecisely known domains. Such problems arise frequently in engineering design. The principal barrier to the general use of EAs for those problems is the huge number of function evaluations that is often required. This makes EAs an impractical approach when the function evaluation depends on numerically heavy design analysis tools, for example, finite elements methods. This paper presents the use of kriging interpolation as a function approximation method for the construction of an internal model of the fitness landscape. This model is intended to guide the search process with a reduced number of fitness function evaluations.

Searching for information is an ubiquitous need in today's data-oriented environments. However, a request for search often entails the service and cooperation of tools managing a diversified set of tasks. In this article, we explore how tools in the form of cooperating agents can be deployed for information management. We describe an agent framework called GAME (goal-oriented, agent-managed environment), and focus on how GAME agents search cooperatively for information requested by a user. Cooperative search entails several issues such as coordinating agent activities, maintaining transparency to agent heterogeneity, and designing information formats to be shared among the agents that require examination. This article analyzes these issues and describes how they are handled in the GAME framework. Cooperative search effectively supports collaboration and information sharing not only among agents in a domain, but also among GAME agents developed across domains. We illustrate the application of cooperative search in task-oriented domains such as Manufacturing and Front Office showing how GAME promotes intradomain and interdomain collaboration in a Factory environment.

This article is an attempt to improve the efficiency of procedures for compositional synthesis of design solutions using building blocks. These procedures have found use in a wide range of applications, and are one of the most substantial outcomes of research into automated synthesis of design solutions. Due to their combinatorial nature, these procedures are highly inefficient in solving problems, especially when the database of building blocks for synthesis or the problem size is large. Previous literature often focuses on improving only the algorithm part of a procedure, although it is both its algorithm and database which together determine the overall efficiency of the procedure. This article reports the construction and analysis of an improved algorithm, based on bidirectional search, for efficient compositional synthesis of design solutions using a set of building blocks.

The purpose of this study is to investigate and optimize the dynamics of state transitions during a process of multistage fuzzy control systems. A variation of the methodology for solving the Vehicle Routing Problem, known as the Savings Method, is applied to finding a sequence of controls to maximize the overall performance of multistage control processes. The Savings Method has been modified into a heuristic to traverse state precedence when transitioning from one known system state to another. In addition, the procedure allows for imposing of two different types of precedences (mandatory and optional) among transition states, as well as a pair of fuzzy constraints and goals throughout each stage of the process. As the control of the system progresses, fuzzy goals may be preset or introduced interactively.