We describe a software environment for dynamic optimization using the simultaneous approach. Over the past few years, there has been significant development in the formulation of simultaneous dynamic optimization problems, using collocation on finite elements, and in the solution of the resulting large-scale nonlinear programming problem, using powerful barrier NLP solvers. Here we describe the background of the simultaneous approach as well as the components that make up the formulation and modeling environment, which we call DynoPC. DynoPC incorporates state-of-the-art NLP and DAE solvers along with a powerful automatic differentiation package. Moreover, it has a number of advanced features including model reduction and moving finite elements. Finally, we describe how DynoPC can be interfaced to other environments using Equation Set Objects (ESO) and the MINLP CAPE-OPEN object. All of these concepts are illustrated with three dynamic optimization examples including a large-scale industrial case study. (c) 2006 Elsevier Ltd. All rights reserved.