Craig W. Schmidt

TL;DR: In this article, the authors present several models for the optimal scheduling of testing tasks in the new product development process of an agricultural chemical or pharmaceutical company, where the goal is to maximize the expected net present value of the research, and the scheduling problem is initially formulated as a nonlinear, nonconvex disjunctive program and then reformulated as a mixed integer linear program.

TL;DR: A new technique for computing the exact overall duration of a project, when task durations have independent distributions is presented, and graph reduction techniques by Hopcroft and Tarjan and by Valdes allow the problem to be broken into a series of smaller subproblems, improving computational efficiency.

TL;DR: In this article, the authors describe the optimization of the New Product Development process of DowElanco, an agricultural chemical company, and present an industrial scale, reproducible example to demonstrate that when subject to the assumptions of the academic models, real world problems are more highly structured than randomly generated problems.

TL;DR: In this paper, a real-world scheduling problem concerning the New Product Development process of an agricultural chemical or pharmaceutical company is presented, where a research and development (R&D) department must schedule the tasks needed to bring a new product to market, in the face of uncertainty about the costs and durations of the tasks, and in the income resulting from introducing the new product.