Efftciency Analysis ofLighting Bulbs Using Fuzzy Data Envelopment Analysis

2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE) Pub Date : 2018-08-01 DOI:10.1109/ICCCEEE.2018.8515841

Maysa Gidom, Fawziah A. Abdulla, Özer Uygun

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Abstract

The efficiency of systems with multiple inputs and multiple outputs can be achieved using Data Envelopment Analysis (DEA) which is one of the decision-making tools. In real-world, input and output values of systems to deal with could be fuzzy. This paper shows a result of DEA techniques using fuzzy data assessing different types of equipment (Decision Making Units / DMUs) under uncertainty. Fuzzy DEA (FDEA) technique engages triangular fuzzy numbers to evaluate the performance of three types of light bulbs; Incandescent light bulbs, Light Emitting Diodes bulbs (LED) and Compact Fluorescent light bulbs (CFL). An input-oriented fuzzy BCC model is used to categorize bulbs with respect to their annual operating cost, kilo-watts of electricity, cost per bulb, life span, light output and carbon dioxide emissions per year. The illustrated method shows that only LED bulb is recognized as an efficient DMU with efficiency 1 (unity), while other bulbs types are recognized as inefficient DMUs with efficiency scores less than 1.

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基于模糊数据包络分析的灯泡节能分析

数据包络分析(DEA)是多输入多输出系统的决策工具之一。在现实世界中，要处理的系统的输入和输出值可能是模糊的。本文展示了模糊数据分析技术在不确定条件下对不同类型设备(决策单元/ dmu)的评估结果。模糊DEA (FDEA)技术利用三角模糊数对三种灯泡的性能进行评价;白炽灯泡、发光二极管灯泡(LED)及紧凑型荧光灯泡(CFL)。采用输入导向模糊BCC模型，根据灯泡的年运行成本、千瓦电量、每只灯泡的成本、寿命、光输出和每年二氧化碳排放量对灯泡进行分类。所示的方法表明，只有LED灯泡被识别为效率为1(单位)的高效DMU，而其他类型的灯泡被识别为效率得分小于1的低效DMU。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)

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