Optimization of industrial scale scheduling problems in new product development

This paper describes the optimization of the New Product Development process of DowElanco, an agricultural chemical company. It outlines how DowElanco created a model capturing the effects of four complications present in their New Product Development process. It reviews previous academic work on optimizing a New Product Development process, which has only addressed one of the four complications. An industrial scale, reproducible example is provided to demonstrate that when subject to the assumptions of the academic models, real world problems are more highly structured than randomly generated problems, which provides a computational advantage. This allows much larger problems to be optimized than had previously been reported.