Multi-objective analysis of a component-based representation within an interactive evolutionary design system

Abstract

This article describes research relating to a user-centered evolutionary design system that evaluates both engineering and aesthetic aspects of design solutions during early-stage conceptual design. The experimental system comprises several components relating to user interaction, problem representation, evolutionary search and exploration and online learning. The main focus of the article is the evolutionary aspect of the system when using a single quantitative objective function plus subjective judgment of the user. Additionally, the manner in which the user-interaction aspect affects system output is assessed by comparing Pareto frontiers generated with and without user interaction via a multi-objective evolutionary algorithm (MOEA). A solution clustering component is also introduced and it is shown how this can improve the level of support to the designer when dealing with a complex design problem involving multiple objectives. Supporting results are from the application of the system to the design of urban furniture which, in this case, largely relates to seating design.

A fuzzy integrated methodology for evaluating conceptual bridge design

“…ANN is used to predict the structural design responses which are used further in evaluation of fitness and constraint violation in GA process. Machwe and Parmee (2007) described multi-objective analysis in a user-centered evolutionary design system. The research evaluated both engineering and aesthetic aspects of design solutions during conceptual design phase.…”

“…Wood and Agogino (1996) cited various sources that demonstrate the conceptual design stage, which takes up the initial 10-20% of the total design time, influences the entire design process including costs. Moreover, Xu, Li, Li, and Tang (2005) and Machwe and Parmee (2007) stated poorly conceived design concept can never be compensated by a good detailed design and also the importance of taking correct decisions early on in the design process is now well understood.…”

Metaheuristic design pattern

“…An example of small populations of individuals presented to user for ranking relates to conceptual bridge design [8]. In this example, small populations (i.e.…”

Integrating aesthetic criteria with evolutionary processes in complex, free-form design – an initial investigation

“…Here all objectives except User-Assigned Fitness have a minimum weight of 0.5 (see (8)) whereas U_fit is assigned a weight of 3.0. The population size has been reduced from fifty to twenty individuals to both facilitate user-interaction and to better illustrate the manner in which the user can steer the evolutionary process during these initial experiments.…”

“…These include agent-based construction and repair of population members, Agent-based aesthetic evaluation, an object-based design representation supported by a case-based machine learning subsystem. The reader is directed to [4], [7] and [8] for a detailed description of the resulting interactive evolutionary design environment (IEDE).…”