Reference-Point-Specification-GIHSS

This repository provides the implementation of a greedy inclusion algorithm for greedy inclusion hypervolume-based subset selection, together with utilities for generating and visualizing Lamé (superellipse) curves at high resolution.

The code accompanies a published research work and was used to produce results and figures reported in the paper.

[Reference Point Specification in Greedy Inclusion Hypervolume-based Subset Selection: A Study on Two Objectives] Authors, Full Paper Link.

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Structure

• greedy_algorithm.py Implements a greedy inclusion scheme to solve a subset selection problem. The algorithm incrementally builds a solution by adding elements whose hypervolume contribution is the largest at that moment.

• curve_generation.py Generates Lamé curves with configurable resolution (e.g., n=10,000).

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Usage