工业4.0技术评估:基于鲸鱼优化算法的集成逆向供应链模型

Sharareh Mohajeri, F. Harsej, Mahboubeh Sadeghpour, Jahanfar khaleghi nia
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引用次数: 1

摘要

近年来,希望减少供应链对环境和社会的负面影响的公司已经采用了集成的逆向供应链实践。工业4.0技术辅助的模型和解决方案已经开发出来,将生命周期结束的产品转化为具有不同用途的新产品。有几种不同技术的废物回收方法,根据工业4.0革命的指标和根据技术权重送到回收中心的废物进行选择和加权。替补模型是多目标的,包括运输成本和环境影响最小化和客户响应需求最大化。采用鲸鱼优化算法和NSGA-II算法求解该模型。通过质量、离散度、均匀性、求解时间等指标的比较,将鲸鱼优化和遗传算法得到的结果相互构成。结果表明,鲸鱼算法在所有情况下都具有更高的探索和提取可能点并获得最优解的能力。NSGA-II算法在均匀性和求解时间上也优于whale算法。对求解时间随问题规模增加而变化的研究,再次证实了未被研究问题的NP-hard性质。
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Industry 4.0 technologies assessment: An integrated reverse supply chain model with the whale optimization algorithm
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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