$ show jmejia8/Metaheuristics.jl
Metaheuristics.jl is a Julia library for global optimization implementing various metaheuristic algorithms for single-objective, multi-objective, and combinatorial optimization problems. The library provides a modular architecture with clear separation between core functionality (state management, problem definitions), algorithm implementations (organized by optimization type), operators (selection, crossover, mutation), test problems, performance indicators, and decision-making methods. The primary workflow involves defining an objective function and search space, selecting/configuring an algorithm, and calling the optimize() function to find optimal solutions. The library depends on standard Julia packages and specialized libraries for distance calculations, distributions, and multi-criteria decision-making.
The LLM identified 2 files worth highlighting for reuse:
Implements the hypervolume indicator using the improved dimension-sweep algorithm from Fonseca et al. (2006). This component calculates the volume between a set of points and a reference point in objective space, providing a measure of both convergence and diversity for multi-objective solutions. The implementation is self-contained, correctly handles the complex geometry of hypervolume calculation in multiple dimensions, and could be extracted for use in any multi-objective optimization context with minimal adaptation.
Provides an efficient implementation of the fast non-dominated sorting algorithm (O(mn^2) complexity) used in multi-objective optimization algorithms like NSGA-II. This component includes functions for computing solution ranks, grouping solutions into fronts, sorting populations by rank, and extracting non-dominated solutions. The implementation is well-structured, demonstrates correct application of a classic algorithm, and could be reused in other multi-objective optimization frameworks with minimal changes.