A genetic optimization of injection molding runner balancing /

A new methodology is proposed to solve the runner balancing problem. The proposed methodology avoids problems associated with the traditional approach. The issues associated with runner balancing and the effects of design variables and processing conditions are evaluated. A general methodology for the robust optimization of a practical industrial problem is also developed. The runner balancing problem is optimized employing deterministic and robust schemes and the results were compared and analyzed. This provided insight into robust runner system design. Finally, an existing constrained genetic algorithm, the superiority of feasible points method is modified to include infeasible solutions in the search, based on their distance from the current best feasible point. The revised and standard algorithms are tested on a series of constrained optimization problems, including the runner balancing problem and results are analyzed and interpreted