
This is the initial release of the HS-MOCO library, specifically tailored for solving the Multiobjective Knapsack Problem (MOKP). Features in this Release Three MIP Formulation Strategies for Hypervolume Scalarization: MIQP: Bilinear product formulation using balanced binary-tree reduction. Log: Non-linear formulation utilizing the Log-Sum-Exp (LSE) trick for numerical stability. MILP: Pure linear formulation using McCormick envelopes. MOKP Benchmark Suite: Includes a complete Multiobjective Knapsack Problem (MOKP) implementation and batch testing scripts (test_mokp.sh) to reproduce experimental results. Modern C++20 Architecture: Header-only design with CMake integration and FetchContent dependency management. 📚 Citation If you use this code in your research, please cite our accompanying paper (citation details will be updated upon publication). In the meantime, please link to this repository. 🛠️ Getting Started See the README.md for instructions on building the project, running the MOKP examples, and integrating the library into your own CMake projects.
If you use this software, please cite it as below.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
