A State-of-the-Art Review on Meta-heuristics Application in Remanufacturing

The objective of this study is to present a state-of-the-art review on applications and trends of meta-heuristics for remanufacturing problems. This literature review mainly encompass the most popular and frequently employed meta-heuristics like genetic algorithm, artificial bee colony, particle swarm optimization, ant colony optimization, simulated annealing, tabu search, variable neighborhood search and the hybrid of these approaches. By adopting a systematic procedure consisting of article collection and article selection, this research work selected 123 articles for literature analysis. The selected literature is categorized based on the application area of the remanufacturing problem; meta-heuristics techniques i.e. individual or hybrid meta-heuristics used; and mathematical models objective type (single or multi-objective models); objective function types based on the sustainable dimension (economic, social or environmental objective); objective functions such as minimize cost/time, maximize profit, etc. considered in a single and multi-objective models. Based on the analysis it is found that production planning and scheduling is the most focused application area of remanufacturing followed with reverse logistics. Further, GA is the most popular individual meta-heuristics used for optimization of the problem. The analysis also finds that hybrid meta-heuristics have gained increased attention in the past few years. The majority of the remanufacturing optimization models considered single objective. The present study also suggests several research avenues for further investigation.