Enhancing modified cuckoo search by using Mantegna Lévy flights and chaotic sequences

Abstract

In this paper, we present an improvement of the modified cuckoo search (MCS) method. We focus on a new nest generation from the top nest group. This group of nests assists a better local search. We use Tent map chaotic sequences to replace the constant parameter, inverse golden ratio of MCS. This process aims to find a better solution in case of multi-modal problems. The Cauchy Lévy distribution is replaced by Mantegna Lévy distribution generation. This process assists in finding a better solution in case of uni-modal problems. To construct a more suitable with wider optimization problems and good convergence property, these two concepts are combined together as Improved MCS with Chaotic Sequences algorithm (ICMCS). The proposed algorithm is verified using nineteen constrained optimization problems. The performance of the proposed algorithm is compared with the original MCS algorithms. The optimal solutions obtained in this study are more superior to MCS.