Dow AgroSciences Uses Simulation-Based Optimization to Schedule the New-Product Development Process

Dow AgroSciences has improved its bottom line by using simulation-based optimization to reduce the time and expense of moving a portfolio of products to market. We examined mathematical programming approaches for scheduling new-product development but found that the solution of these formulations is intractable for problems of practical size that include resource constraints. We developed a simulation-based framework for generating feasible solutions, which can be used with any heuristic optimization approach (for example, tabu search or genetic algorithms). The heuristic optimization algorithms operate on a solution space consisting of the precedence relationships among activities in the new-product development process. The firm implemented this approach via a Six Sigma project. From 1998 to 2004, it saved several million dollars based on the schedules determined using simulation-based heuristic optimization.