A Review of Nature-Based Algorithms Applications in Green Supply Chain Problems

Abstract

Abstract-In the recent years, there is a significant attention among researchers and practitioners to environmental issues and green supply chain (GrSC) because of legislations and profit oriented motivations.Because of considering environmental issues GrSC besides the economic variables, the models are very difficult to find optimal. Hence, complicated green problems call for development of modern optimization methods and algorithms to solve optimization models by efficient techniques. In recent decades, meta-heuristic algorithms have been developed to overcome the problem that most of them are inspired from nature. Some of the algorithms have been inspired from natural generation, some of them inspired from swarm behavior, and others simulate natural processes. In this research we summarize the recent advance evolutionary optimization algorithms and swarm intelligence algorithms which are applied to GrSC and green logistics. Literature reviewed in this paper shows the current state of the art and discusses the potential future research trends.Index Terms-Evolutionary algorithms, green supply chain, meta-heuristic, swarm intelligence algorithms.

Analyzing energy consumption of nature-inspired optimization algorithms

“…Existing nature-inspired algorithms research primarily addresses the following areas of research: optimization [1, 2, 60, 61] using metaheuristics [62] or heuristics [63] approaches; greening processes, for example greening the supply chain [64], smart energy management [65], data center energy efficiency [66]; energy efficiency [67] and energy optimization [68] in wireless sensor network clustering. Our critical literature review has shown that to date, there is no research on energy efficient natureinspired algorithms and thus, our research aims to address this identified gap.…”