Rafflesia Optimization Algorithm Applied in the Logistics Distribution Centers Location Problem

Abstract

Intelligent evolutionary algorithm is an important method to solve optimization problems. Most of their inspiration comes from the laws of nature and biology. This paper proposes a new intelligent evolutionary algorithm based on the life habits of Rafflesia, which is called Rafflesia Optimization Algorithm. It mainly consists of three stages: attracting insects, swallowing insects, and spreading seeds. In the first stage, the ROA algorithm performs the local search to find the optimal solution. In the second stage, it improves execution efficiency and solution accuracy by reducing the number of individuals. In the third stage, it performs the global search to jump out of the local optimal position. In the experimental part, this paper uses numerical functions (the CEC2013 benchmark function set) and practical application problems (the logistics distribution centers location problem) to test the performance of the ROA algorithm, and compares it with seven meta-heuristics algorithms. The experimental results prove the effectiveness and practicability of the ROA algorithm.