Projects with sequential iteration: Models and complexity

Abstract

Many New Product Development (NPD) projects are inherently complex, making effective management of the tasks, resources, and teams necessary to bring new products to market problematic. Frequently, managers of NPD projects are overwhelmed by complicating factors such as stochastic task times, ill-defined specifications, complex interrelationships between tasks, and information dependencies. Recently, an alternative project management tool called the Design Structure Matrix (DSM) that explicitly takes into account the iterative nature of NPD projects has been proposed. In this paper, we first introduce a mixed-integer linear programming formulation for the numerical DSM. Then, we analyze the numerical DSM and establish the complexity of this class of problems. Finally, numerical analysis of the DSM problem and heuristic approaches is presented that shows that relatively good solutions can be easily obtained, thereby offering managers an efficient alternative solution approach to the original DSM problem.

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