Integer programs for solving time-dependent models—models in which decisions have to be made about the times at which activities occur and/or resources are utilized—are pervasive in industry, but are notoriously difficult to solve. In the last few years, interest in the role of discretization in approaches to solve these problems has intensified. One novel paradigm, dynamic discretization discovery, has emerged with the potential to greatly enhance the practical tractability of time-dependent models using integer programming technology. We introduce dynamic discretization discovery, illustrate its use on the traveling salesman problem with time windows, highlight its core principles, and point to opportunities for further research. Relations to other approaches for tackling time-dependent models are also discussed.
https://doi.org/10.1007/s11750-019-00514-4Cite as:
@article{Boland_2019,
doi = {10.1007/s11750-019-00514-4},
url = {https://doi.org/10.1007%2Fs11750-019-00514-4},
year = 2019,
month = {may},
publisher = {Springer Science and Business Media {LLC}},
volume = {27},
number = {2},
pages = {147--173},
author = {Natashia L. Boland and Martin W. P. Savelsbergh},
title = {Perspectives on integer programming for time-dependent models},
journal = {{TOP}}
}