Meliorated Crab Mating Optimization Algorithms for Capacitated Vehicle Routing Problem

Abstract

This study proposes a new metaheuristic optimization algorithm, inspired by crabs mating in nature, with five versions. For these crab versions, first, the code of the crab mating optimization algorithm was written, inspired by Chifu’s crab mating optimization paper. It has been observed that the original crab mating algorithm gives successful results; however, works very slowly and there are some parameters that are not used in the algorithm, and the mating probability of crabs converges to either 100% or 0%. Considering that the crab mating algorithm gives good results, new crab versions have been developed from this algorithm. The improved crab algorithms are compared with 4 popular metaheuristic algorithms for 20 different benchmark functions on metrics, such as mean, standard deviation, optimality, accuracy, run time, and the number of function evaluations (NFE). According to the results obtained, the proposed crab versions give as good results as the popular algorithms. In the last part of the study, the proposed algorithms were adapted for capacitated Vehicle Routing Problem (VRP) which is one of the real-world optimization problems, and their performances on this problem were compared among themselves. As a result of this comparison made on the VRP, the Meliorated Adaptive Crab mating optimization algorithm (MAC) algorithm gave more successful results in terms of speed and performance than the other proposed crab versions. Due to the performance of the proposed algorithms, we expect these algorithms to be applied to different optimization problems. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.