sangminwoo / evo_ai

Evolutionary Algorithms (knapsack problem, traveling salesman problem, 4bit deceptive problem, neural network architecture optimization)

Genetic / Evolutionary Algorithms

• Introduction to Genetic Algorithms
• Knapsack Problem
• Traveling Salesman Problem
• 4bit Deceptive Problem
• Neural Network Architecture Optimization

Knapsack Problem

Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible.

Traveling Salesman Problem

The travelling salesman problem (also called the traveling salesperson problem or TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?"

4bit Deceptive Problem

Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global optimum.

Neural Network Architecture Optimization

Optimize the NN structure in terms of minimizing the number of connections (i.e., weights or edges) among neurons by using a customized GA, while maintaining the classification accuracy as much as possible.