A CONSTRAINT-BASED GENETIC ALGORITHM FOR CONCURRENT ENGINEERING

Concurrent engineering is a complex problem in that a large number of considerations have to be brought to bear during the design stage. Com pounding this complexity is that concurrent engineering problems are a lso likely to encompass both numeric and symbolic variables, and const raints that range from simple algebraic constraints, through condition al constraints, to potentially very complex database constraints. Prev ious approaches have concentrated on finding good solutions to simplif ied problems or, alternatively, to finding a feasible solution which m ay not be close to optimal. This paper presents an approach to concurr ent engineering problems that extends the conventional genetic algorit hm approach to handle the complex variety of variables and constraints that are inherent in a typical concurrent engineering problem. This p oses some severe research challenges and this paper describes three ge netic operators (the constraint-based initialization, crossover, and m utation operators) that preserve feasibility during initialization, cr ossover, and mutation. Preserving feasibility is achieved by incorpora ting local constraint propagation, boundary propagation, and set propa gation. This overall approach is called the constraint-based genetic a lgorithm (CBGA) and aims to determine a near-optimal solution to concu rrent engineering problems. The paper describes the background to cons traint modelling, and genetic algorithms. The constraint-based initial ization, crossover and mutation operators are then detailed, together with a description of the implementation of the CBGA in a system calle d Comet. Finally an example application is given.