Search Results for "binary differential evolution"

The ASCO project aims to bring circuit optimization capabilities to existing SPICE simulators using a high-performance parallel differential evolution (DE) optimization algorithm. It supports Eldo, HSPICE, LTspice, Spectre, and Qucs.

...It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer

Implementation of Point Symmetry-based Automatic Clustering Approach Using Differential Evolution Using bug fixed KD tree nearest neighbor search from https://github.com/CristianDallos/kmeansclustering. (It is also modified to search for multiple nearest points instead only for one.) Used those academic works for algorithm implementation: http://cs.cug.edu.cn/teacherweb/gwy/Publication/ISICA-09.pdf http://www.isical.ac.in/~sanghami/ieeetkde_cameraready.pdf http://www.softcomputing.net/smca-paper1.pdf 1. ...

Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process.