I am very pleased to announce that our latest paper entitled “An Integrated Solver for Optimization Problems” has been accepted for publication in Operations Research. Here’s the news story:
Optimization problems come in different varieties that make them more amenable to one solution approach over another. For some of these problems, however, no single approach is capable of obtaining satisfactory results. In such cases, recent research suggests that the right combination (or integration) of different technologies can simplify modeling and speed up computation substantially. Unfortunately, integration often requires the development of special purpose computer code, which is time-consuming and error-prone. In “An Integrated Solver for Optimization Problems”, Tallys Yunes, Ionut D. Aron and John N. Hooker combine mixed-integer linear programming, constraint programming, and global optimization in a single system. They propose a general-purpose integrated modeling and solution framework called SIMPL, which views traditional approaches as special cases of a more general solution method. Their computational experiments involve a variety of problems such as production planning, product configuration, machine scheduling, and truss structure design. With concise models written in SIMPL’s high-level modeling language, they show that the results obtained with special purpose computer codes can be matched, and sometimes improved upon, with a fraction of the implementation effort.
I am especially thankful to the anonymous referees, the associate editor, and the area editor, whose comments helped improve the quality of the paper.