The Applications of Nature-Inspired Algorithms in Logistic Domains: A Comprehensive and Systematic Review

Abstract

The utilization of nature-inspired algorithms for logistic domains and its potential to manage uncertainty evolve solutions and conduct optimization leftovers to be an antecedent research domain. The present article has considered primary bio-inspired processes to solve the logistics problem systematically until Feb 2020. We have opted 36 articles to summarize and review. The significant algorithm has been ranked into five primary categories: ant colony optimization, particle swarm optimization, memetic algorithm, genetic algorithm, and artificial bee colony. It is evident from the outcomes that within the past 10 years, bio-inspired procedures have experienced fast progress. They have prosperously been applied for optimization and design of particularly intricate systems like logistics distribution systems. It can be deducted from the outcomes that the other algorithms in the logistics distribution’s optimization have to be enhanced, leading to the elevation of the effectiveness of logistics enterprises. Also, the policy assistance for the logistics organization has been empowered to boost the efficient and healthy progress of it. We can observe that the genetic algorithm and its hybrids have indicated the best efficiency until now. So, it is essential to investigate the logistics distribution route optimization by recent nature-inspired algorithms for optimizing the logistics and selecting a rational distribution scheme.