Sequential simplex optimization is an evolutionary operation (EVOP) method of carrying out designed experiments to achieve desired quality characteristics for a product or process. In contrast to traditional Box-type EVOP which typically requires 2k initial experiments and approximately 1/2 x 2k experiments for each additional iteration (where k is the number of variables or factors), sequential simplex optimization requires only k+1 initial experiments and only one or two experiments for each additional iteration. The history, theory, and applications of the sequential simplex methods will be discussed.

Sequential simplex optimization: A method for the rapid development of products and processes

247th National Meeting (2014)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.