Abstract

In recent years, integrated reverse supply chain practices have been adopted by companies that desire to reduce the negative environmental and social impacts within their supply chains. models and solutions assisted by industry 4.0 technologies have been developed to transform products in the end of their life cycle into new products with different use. There are several methods with different technologies to recycle the wastes, which have been selected and weighted based on the indicators of the industry 4.0 revolution and the wastes sent to recycling centers based on the technology weight. The understudy model is multi-objective, including minimizing transportation costs and environmental effects and maximizing customer response demand. The whale optimization algorithm and the NSGA-II algorithm were also used to solve this model. The results obtained from whale optimization and genetic algorithms have been comprised of each other through comparative indicators of quality, dispersion, uniformity, and solving time. The results showed that the whale algorithm has a higher ability to explore and extract possible points and achieve optimal solutions in all cases. The NSGA-II algorithm was also superior to the whale algorithm in terms of uniformity and solving time. The investigation of changes in solving time with increasing problem size was another confirmation of the NP-hard nature of the understudied problem.

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