Literature Review on Sustainable Renewable Energy Supply Chain Optimization A Focus on Heuristic and Metaheuristic Methods

Abstract

The transition towards sustainable energy systems has necessitated the optimization of renewable energy supply chains. This literature review aims to explore the state-of-the-art approaches, with a specific focus on heuristic and metaheuristic methods, employed for optimizing sustainable renewable energy supply chains. Metaheuristics, which are higher-level strategies for guiding search processes, have demonstrated great potential in tackling complex optimization problems with diverse constraints and objectives. Genetic algorithms, simulated annealing, ant colony optimization and particle swarm optimization are some of the examples for the metaheuristic methods. The review emphasizes their ability to provide near-optimal solutions, handle uncertainties, and optimize multiple conflicting objectives. This literature review synthesizes and analyzes the existing research on heuristic and metaheuristic methods for optimizing sustainable renewable energy supply chains.