Ant Colony Optimization Algorithm Implementation for TSP Problem
Implementation of the Traveling Salesman Problem Optimization Using Ant Colony Algorithm
UAV Path Planning
UAV path planning involves finding optimal or feasible routes from starting points to target destinations under specific constraints while meeting performance indicators. The core challenge is solving multi-objective optimization problems with multiple constraints. Developing routes that satisfy mission requirements, navigation constraints, and safety standards significantly enhances UAV weapon system performance. This research summarizes UAV path planning frameworks, investigates static global planning and dynamic local planning methodologies, analyzes commonly used planning algorithms, and provides future research directions with implementation considerations.
Particle Swarm Optimization MATLAB Implementation
MATLAB implementation of Particle Swarm Optimization algorithm for solving optimization problems with nonlinear constraints
MATLAB Optimization: Combining Niche Algorithm with Ant Colony Algorithm
Implementation of Combined Niche and Ant Colony Algorithm for MATLAB Optimization Problems - Fully Functional Code
MATLAB Implementation of Ant Colony Algorithm for Continuous Function Optimization Problems
MATLAB program implementation of ant colony optimization algorithm for solving continuous function optimization problems, featuring parameter adjustment strategies and performance enhancement techniques.
Genetic Algorithm for Optimizing Multi-Objective Course Scheduling Problems
Genetic algorithm serves as an effective optimization method for solving multi-objective course scheduling challenges, featuring robust search capabilities and flexible constraint handling.
Genetic Algorithm for Optimal Power Flow (OPF) Optimization
Implementation of Genetic Algorithm for Solving Optimal Power Flow Optimization Problems with Code Integration
Fundamental Particle Swarm Optimization (PSO) Algorithm for Solving Optimization Problems
Fundamental Particle Swarm Optimization (PSO) Algorithm for Solving Optimization Problems with Code Implementation Insights
Direct Search Methods in Optimization Problems
Direct search methods in optimization problems can operate without gradient information, unlike many other optimization approaches that require derivative calculations.
Quantum-Inspired Evolutionary Algorithm (QEA) - A Rising Optimization Approach in Recent Years
Quantum-Inspired Evolutionary Algorithm (QEA), gaining significant popularity over the past two years for solving general optimization problems, with a implementation example focusing on the classic knapsack problem (discrete binary optimization).