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Peer-reviewedCC BY 4.0Operations Research Letters

A computational comparison of handling distance constraints in MINLP

  • Christopher Hojny
  • Leo Liberti
Open at sourcePDFDOICite

Abstract

Minimum distance constraints (minDCs) appear in many geometric optimization problems. They pose major challenges for mixed-integer nonlinear programming (MINLP) due to their reverse-convexity. We develop new algorithms for tightening variable bounds in general MINLPs with minDCs. Because many such problems exhibit substantial symmetry, we further discuss an approach for handling rotation symmetries. In a computational study, we examine the performance of the various methods and determine the scenarios in which each approach demonstrates superiority.

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Cite

BibTeXRIS
BibTeX
@article{hojny2026computational,
  title = {{A computational comparison of handling distance constraints in MINLP}},
  author = {Christopher Hojny and Leo Liberti},
  journal = {Operations Research Letters},
  year = {2026},
  month = oct,
  doi = {10.1016/j.orl.2026.107533},
  url = {https://hal.science/hal-05775997v1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A computational comparison of handling distance constraints in MINLP
AU  - Christopher Hojny
AU  - Leo Liberti
PY  - 2026
DA  - 2026/10/02
JO  - Operations Research Letters
DO  - 10.1016/j.orl.2026.107533
UR  - https://hal.science/hal-05775997v1
AB  - Minimum distance constraints (minDCs) appear in many geometric optimization problems. They pose major challenges for mixed-integer nonlinear programming (MINLP) due to their reverse-convexity. We develop new algorithms for tightening variable bounds in general MINLPs with minDCs. Because many such problems exhibit substantial symmetry, we further discuss an approach for handling rotation symmetries. In a computational study, we examine the performance of the various methods and determine the scenarios in which each approach demonstrates superiority.
SN  - 0167-6377
SN  - 1872-7468
ER  -