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一种用于型煤生产中生物质材料有效评估和排序的DEAV-BWM组合方法。

A combined DEAV-BWM approach for effective evaluation and ranking of biomass materials in charcoal briquette production.

作者信息

Wichapa Narong, Nasawat Pariwat, Kanchanaruangrong Nattapat, Choompol Atchara

机构信息

Department of Industrial Engineering, Faculty of Engineering and Industrial Technology, Kalasin University, Kalasin 46000, Thailand.

Department of Logistics and Process Engineering, Faculty of Industrial Technology, Rajabhat Rajanagarindra University, 24000, Thailand.

出版信息

MethodsX. 2024 Nov 28;13:103075. doi: 10.1016/j.mex.2024.103075. eCollection 2024 Dec.

Abstract

The utilization of agricultural waste for producing charcoal briquettes is gaining significant attention as a sustainable alternative energy source. Converting these residues into charcoal briquettes not only addresses energy shortages but also provides an efficient solution for managing agricultural waste, contributing to environmental sustainability. This study proposes a novel methodology integrating a Data Envelopment Analysis Variant (DEAV) with the Best-Worst Method (BWM) to assess and rank biomass materials for charcoal briquette production. The DEAV-BWM model enhances the evaluation process by considering multiple criteria simultaneously and incorporating both efficiency and consensus among different evaluation methods. The key highlights of the methodology are as follows:•A novel method, called the DEAV model, for evaluating efficiency scores has been established, incorporating both Data Envelopment Analysis (DEA) and Multi-Attribute Decision Making (MADM) concepts.•This paper introduces a novel hybrid method that combines the DEAV model with the BWM to evaluate and rank biomass materials for charcoal briquette production, enhancing the reliability and robustness of the decision-making process.•The proposed method can be adapted and applied to other areas of biomass utilization and beyond, providing a versatile tool for researchers and practitioners in the field of sustainable energy, engineering, and operations research.

摘要

将农业废弃物用于生产炭块作为一种可持续的替代能源正受到广泛关注。将这些残留物转化为炭块不仅能解决能源短缺问题,还为农业废弃物管理提供了一种有效解决方案,有助于实现环境可持续性。本研究提出了一种将数据包络分析变体(DEAV)与最佳 - 最差方法(BWM)相结合的新方法,用于评估和排序用于炭块生产的生物质材料。DEAV - BWM模型通过同时考虑多个标准并结合不同评估方法之间的效率和一致性来增强评估过程。该方法的主要亮点如下:

• 建立了一种名为DEAV模型的新方法来评估效率得分,该方法融合了数据包络分析(DEA)和多属性决策(MADM)的概念。

• 本文介绍了一种将DEAV模型与BWM相结合的新型混合方法,用于评估和排序用于炭块生产的生物质材料,增强了决策过程的可靠性和稳健性。

• 所提出的方法可以进行调整并应用于生物质利用及其他领域,为可持续能源、工程和运筹学领域的研究人员和从业者提供了一种通用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16b0/11650255/59d7d1d7cace/ga1.jpg

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