In computer-aided drafting and design, interactive graphics is used to design components, systems, layouts, and structures. There are several approaches for using automated graphical layout tools currently. Our approach employs a genetic algorithm to implement a tool for automated 3D graphical layout design and presentation. The effective use of a genetic algorithm in automated graphical layout design relies on defining a fitness function that reflects user preferences. In this paper, we describe a method to define fitness functions and chromosome structures of selected objects. A learning mechanism is employed to adjust the fitness values of the objects in the selected layout chosen by the user. In our approach, the fitness functions can be changed adaptively reflecting user preferences. Experimental results revealed good performance of the adaptive fitness functions in our proposed mechanism.

We have developed an advanced tool for dimensioning circuit-switched networks, called CNEP (Circuit-Switched Network Evaluation Program) , for effective design of digital networks. CNEP features a high-reliability network structure (node dispersion, double homing, etc) , both-way circuit operation, and circuit modularity (or big module size), all of which are critical for digital networks. CNEP also solves other dimensioning problems such as the cost difference between existing and newly installed circuits, and handles multi-hour traffic conditions, dynamic routing, and multiple-switching-unit nodes. Operations Research techniques are applied to produce exact and heuristic algorithms for these problems. Algorithms with good time-performance trade-off characteristics are chosen for CNEP.