MEACCP: A membrane evolutionary algorithm for capacitated clustering problem

Abstract

The Capacitated Clustering Problem (CCP) is a constrained clustering problem with a wide range of applications in VLSI design, vehicle routing, and mail delivery. In order to improve the performance of solving CCP, this paper proposes a membrane evolutionary algorithm MEACCP based on the Membrane Evolutionary Algorithm Framework (MEAF). First, the membrane structure of MEACCP and its object representation are designed. Second, six evolution operators are designed to evolve objects within the membrane and membrane structures. Third, the MEACCP and the method of membrane population initialization are discussed. Finally, MEACCP experiments were conducted on 100 instances of four different types of benchmark datasets, and the experimental results were compared with the results of the current state-of-the-art CCP algorithms. The experimental results show that the number of instances where MEACCP can find the optimal solution is 4.3 ∼ 9.1 times that of the algorithms in comparison, and the stability is better than all comparison algorithms.