Ranking and Selection of Water Meters With the Technique of Multi Attribute Decision Making; Entropy and TOPSIS

Subject Areas : Article frome a thesis

Mahdi Nakhaeinejad ¹ , Ahmad Sartipzadeh ²

1 - Department of Industrial Engineering, Yazd University, Yazd, Iran
2 - Department of Industrial Engineering, Science and Arts University, Yazd, Iran

Received: 2019-06-27 Accepted : 2021-04-26 Published : 2021-04-21

Keywords: TOPSIS, multi-criteria decision-making, entropy, Water meter, Decision making models,

Abstract :

Introduction:Choosing a water meter for a household is one of the major issues in water and wastewater companies. In recent years, due to the increase in the number of subscribers, increase in the number of accident due to the inadequacy of water meters, also various parameters of the water meter and environmental and regional conditions, the selection of water meters is more evident. The decision maker needs to select the most suitable water meter to achieve the desired output at a lower cost and his ability.
Materials and Methods:Studies show that there is no research on the use of MADM techniques in the field of water meter selection for household use. In the research of industrial and volumetric meters, also only a few parameters have been investigated and according to the researcher's opinion, the solution has been presented without considering the quantitative effect of factors. In the present research, first, the key attribute for evaluation of the meters are identified. Then based on the Entropy method and opinion of industry experts, the weight of criteria is calculated. Then, TOPSIS technique attempts to present a strategy for water and wastewater companies to choose suitable meters for home appliances.
Findings:Finally, the calculations for meters’ attribute determine the relative importance of attribute and also water meter ranking, which can be used for selection of the water meters.
Conclusion:According to the results of this research, the order for selecting the water meters is presented, that semiconductor multi-jet meters ranked in the first order.

References:

1.       Yazdandoost F, Izadi A. An asset management approach to optimize water meter replacement. Environmental Modelling & Software. 2018; 104: 270-281. [https://doi.org/10.1016/j.envsoft.2018.03.015]

2.       Tabesh M, Ali-Bariany E, Motevallian S, Roozbahani A, Beygi S. Prioritization of Water Consumption Management Strategies in Water Distribution Networks Using Multiple Criteria Decision Making Method of Fuzzy Analytic Hierarchy Process (Case Study: Tehran). Amirkabir Journal of Civil Engineering. 2017; 49(1): 47-56. [doi: 10.22060/ceej.2015.379].

3.       Michaud D., Apostolakis G E. Methodology for Ranking the Elements of Water-Supply Networks. Journal of Infrastructure Systems. 2006, 12(4), 230–242. [doi:10.1061/(asce)1076-0342(2006)12:4(230)].

4.       Morais D C, de Almeida A T. Group decision-making for leakage management strategy of water network. Resources, Conservation and Recycling. 2007, 52(2), 441–459. [https://doi.org/10.1016/j.resconrec.2007.06.008]

5.       Berg S, Lin C. Consistency in performance rankings: the Peru water sector. Applied Economics. 2008, 40(6), 793–805. [https://doi.org/10.1080/00036840600749409]

6.       Kavousian A, Rajagopal R, Fischer M. Ranking appliance energy efficiency in households: Utilizing smart meter data and energy efficiency frontiers to estimate and identify the determinants of appliance energy efficiency in residential buildings. Energy and Buildings. 2015; 99, 220–230. [DOI: 10.1016/j.enbuild.2015.03.052]

7.       Zyoud S. H., Shaheen H., Samhan S., Rabi A., Al-Wadi F., Fuchs-Hanusch, D. Utilizing analytic hierarchy process (AHP) for decision making in water loss management of intermittent water supply systems. Journal of Water, Sanitation and Hygiene for Development. 2016; 6(4), 534–546. [https://doi.org/10.2166/washdev.2016.123]

8.       Zyoud S H, Kaufmann L G, Shaheen H, Samhan S, Fuchs-Hanusch D. A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Systems with Applications. 2016; 61, 86–105. [https://doi.org/10.1016/j.eswa.2016.05.016]

9.       Rajabi G., Ostad-Ali-Askari K., Eslamian S, Singh V, Dalezios N. Non-Accounted Water Assessment at the Level of water distribution Networks in Isfahan's Small communities, Isfahan, Iran. Journal of Environmental Research. 2018; 2, 1:4. [https://www.researchgate.net/publication/327966435_Non-Accounted_Water_Assessment_at_the_Level_of_Water_Distribution_Networks_in_Isfahan%27s_Small_Communities_Isfahan_Iran]

10.   Mohammed H J, Kasim M M, Shaharanee I N M. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights. AIP Conference Proceedings. 2017; AIP Publishing, 040019. [DOI:10.1063/1.5012207]

11.   Biswas P, Pramanik S, Giri B C. TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural computing and Applications. 2016; 27, 727-737. [https://doi.org/10.1007/s00521-015-1891-2]

12.   Ardakani Z, Bartolini F, Brunori G. Food and nutrition security in Iran: application of TOPSIS technique. New Medit. 2017; 16, 11-17. [https://www.researchgate. net/publication/315713361_Food_and_nutrition_security_in_Iran_Application_of_TOPSIS_technique]