Using the design of bicycle frames as a case study, this paper explores the potential of a multiobjective extension of the shape annealing approach to conceptual design. The key elements of this approach are a randomized search based optimization method (to simulate creativity), a generative structural shape grammar (to allow different configurations to be explored), and a multiobjective optimization approach (to identify competing concepts occupying different parts of the trade-off surface). The results presented demonstrate the success of this approach in exploring a multiplicity of different design configurations and presenting the designer with a variety of Pareto-optimal concepts worthy of further consideration.@en

This paper describes a novel implementation of the Simulated Annealing algorithm designed to explore the trade-off between multiple objectives in optimization problems. During search, the algorithm maintains and updates an archive of non-dominated solutions between each of the competing objectives. At the end of search, the final archive corresponds to a number of optimal solutions from which the designer may choose a particular configuration. A new acceptance probability formulation based on an annealing schedule with multiple temperatures (one for each objective) is proposed along with a novel restart strategy. The performance of the algorithm is demonstrated on three examples. It is concluded that the proposed algorithm offers an effective and easily implemented method for exploring the trade-off in multiobjective optimization problems.@en