Part 1: Basic concepts of Intelligent Water Droplet Algorithm (IWD)
1 Introduction
In the fields of computer science and engineering, the task of finding optimal solutions is often one of the most critical tasks. There are a variety of heuristics and metaheuristics available for these problems. Among them, the intelligent water droplet algorithm (IWD) is a new algorithm that has attracted attention in recent years. It is inspired by the interaction between water flow and river beds in nature. In this article, we will introduce the IWD algorithm in detail and show how to use Python to solve the classic Traveling Salesman Problem (TSP).
2. Overview of Intelligent Water Droplet Algorithm (IWD)
The intelligent water drop algorithm is a method that simulates the flow of natural water droplets on the river bed to find the optimal path. When a drop of water flows on the river bed, it chooses a path based on the terrain and obstacles on the river bed. Similarly, the IWD algorithm simulates the flow of water droplets through a problem solution space to find the optimal solution.
3. Basic principles of IWD
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Soil Renewal Mechanism : Every time a water droplet flows through a path, it changes the "soil" content of that path. In TSP, soil can be viewed as the weight or cost of a path. The more water droplets flow through a path, the less soil there will be in the path, making the path more attractive.
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Randomness and evaporation : To avoid all water droplets flowing along the same path, IWD introduces randomness and evaporation mechanisms. This ensures diversity in the search space and allows the algorithm to explore more possible solutions.
Below we will discuss in detail how to use Python to implement the IWD algorithm and solve the Traveling Salesman Problem (TSP).
# 初始化参数和导入库
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