Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran.
J Environ Manage. 2020 Jun 15;264:110428. doi: 10.1016/j.jenvman.2020.110428. Epub 2020 Mar 20.
Nowadays, preferred compromise response of renewable energies' demands regarding the candidate sustainable feedstocks is a crucial issue for market change management. Thus, selecting the most suitable sustainable feedstock is a key factor for optimum renewable products allocation problem. To address the issue, this study proposes a hybrid adaptive framework based on consensus evaluation approach, weighting and ranking procedure, and preferred demand assignment under dynamic hesitant fuzzy sets. In this respect, the consensus evaluation approach is tailored regarding the direct and indirect feedback mechanisms to enhance the quality evaluation of candidate sustainable feedstocks under assessment criteria. Thereby, the weight of each criterion is determined based on the developed dynamic hesitant fuzzy entropy method and the candidate sustainable feedstocks are ranked with respect to developed dynamic hesitant fuzzy positive and negative ideal solutions. Then, a revised multi-choice goal programming model is extended regarding the dynamic hesitant fuzzy closeness indexes to attend to preferred compromise response of demand centers by optimum renewable products allocation. Meanwhile, the presented hybrid adaptive framework is implemented to a real case study to represent the applicability and efficiency of the proposed approach. Furthermore, a comparative analysis is provided by defining eight comparison indexes to compare the obtained results with two recent studies in relevant literature for representing the validation and verification of the proposed approach. The comparative analysis shows that the proposed approach versus the two other approaches has merits such as modeling of uncertainty, experts' weights, adaptive structure, unanimous agreement-based approach, and last aggregation framework. Finally, a sensitivity analysis is represented to show the sensitiveness and robustness of the obtained results from changing the criteria weights, goals values, and consensus elimination. Thereby, the sensitivity analysis indicates that the obtained ranking results are sensitive to sustainability criteria unlike the technical criterion.
如今，可再生能源需求对候选可持续原料的首选妥协响应是市场变化管理的一个关键问题。因此，选择最合适的可持续原料是优化可再生产品分配问题的关键因素。针对这个问题，本研究提出了一种基于共识评估方法、权重和排序程序以及动态犹豫模糊集下首选需求分配的混合自适应框架。在这方面，共识评估方法针对直接和间接反馈机制进行了定制，以增强评估标准下候选可持续原料的质量评估。因此，根据所提出的动态犹豫模糊熵方法确定每个标准的权重，并根据所提出的动态犹豫模糊正理想和负理想解对候选可持续原料进行排序。然后，针对动态犹豫模糊接近度指数，扩展了修订后的多目标规划模型，以关注需求中心的首选妥协响应，实现最优的可再生产品分配。同时，将所提出的混合自适应框架应用于一个实际案例研究，以展示所提出方法的适用性和效率。此外，通过定义八个比较指标进行了比较分析，将得到的结果与相关文献中的两个最新研究进行了比较，以验证所提出方法的有效性和可靠性。比较分析表明，与另外两种方法相比，所提出的方法具有建模不确定性、专家权重、自适应结构、基于一致同意的方法和最后聚合框架等优点。最后，进行了敏感性分析，以显示从改变标准权重、目标值和共识消除的角度获得的结果的敏感性和稳健性。敏感性分析表明，与技术标准相比，所得排名结果对可持续性标准敏感。
