Multiobjective optimization of component placement on printed wiring boards

This paper presents a solution methodology for multiobjective optimization problems in the context of models for the placement of components on printed wiring boards. The methodology combines the use of a flow and heat transfer solver, a genetic algorithm for the adaptive search of optimal or near-optimal solutions, and a multiobjective optimization strategy (Pareto optimization or multiattribute utility analysis). Using as the optimization criterion the minimization of an estimate of the failure rate of the system of components due to thermal overheating (via an Arrhenius relation), the effectiveness of the present solution methodology is demonstrated by reference to a case with known optimal solutions. The results obtained using the same solution methodology for a multiobjective optimization problem (a variation of the case study) involving the minimization of the aforementioned total failure rate of the system as well as the minimization of the total wiring length (given some interconnectivity requirements) are presented and discussed for both Pareto optimization and multiattribute utility analysis