The best available technology for small electroplating plants applying analytical hierarchy process

Dabaghian, M. R.; Hashemi, Seyed Hossein; Ebadi, Taghi; Maknoon, Reza

doi:10.1007/bf03326044

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…MCDM in such cases can consider various criteria and apply them in selecting and ranking the strategies. Several methods have been proposed for MCDM; of these, the AHP model has been accepted by many researchers and has been widely used in different cases (Srdjevic, 2007;Ananda and Herath, 2008;Dabaghian et al, 2008;Gharedaghi et al, 2011;Montazar and Gaffari, 2012). The TOPSIS model is also a useful technique for dealing with multi-criteria decision problems (Hwang and Yoon, 1981).…”

Section: Multi-criteria Decision Making (Mcdm)mentioning

confidence: 99%

Decision Models for the Ranking of Agricultural Water Demand Management Strategies in an Arid Region

Banihabib

Shabestari

2017

Irrigation and Drainage

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The agricultural sector is the largest consumer of water and its demand management has a significant impact on water resources of arid areas. This research proposes a hybrid multi‐criteria decision‐making (MCDM) model to prioritize agricultural water demand management (AWDM) strategies based on surveys carried out with 35 Iranian experts in an arid region. It hybridized the advantages of the modified technique for order preference by similarity to ideal solution (MTOPSIS) and the analytical hierarchy process (AHP) methods, and it is called MTAHP. The AHP model is used to determine the relative weights and consistency ratio assessment and finally the MTOPSIS model is used to rank the strategies. Moreover, ELimination and Choice Expressing REality III (ELECTRE III) as a non‐compensatory model and simple additive weighting (SAW) as a compensatory model were used for comparison with the proposed model. The proposed model result was similar to the SAW model but different from ELECTRE III. High‐ranked strategies are training farmers, improvement of cropping patterns and land levelling and modernization of the irrigation systems in the region, respectively. The results of this research show the ability of the hybrid model of AHP and MTOPSIS to prioritize the strategies for AWDM which is recommended for other similar regions. Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Multi-criteria Decision Making (Mcdm)mentioning

confidence: 99%

Decision Models for the Ranking of Agricultural Water Demand Management Strategies in an Arid Region

Banihabib

Shabestari

2017

Irrigation and Drainage

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“…• brand selection (Ultrasonic Scanning Machine (Montevechi, Guimaraes, Oliveira, & Friend, 2010), neonatal ventilators (Sloane, Liberatore, Nydick, Luo, & Chung, 2003)), • site selection and allocation (landfill site (Hasan, Tetsuo, & Islam, 2009;Javaheri, Nasrabadi, Jafarian, Rowshan, & Khoshnam, 2006;Yahaya, Ilori, Whanda, & Edicha, 2010), sustainable coastal tourism (Abed, Monavari, Karbasi, Farshchi, & Abedi, 2011), railway station (Mohajeri & Amin, 2010)), • technology selection (waste water treatment for electroplating industry (Dabaghian, Hashemi, Ebadi, & Maknoon, 2008), solar thermal collection technology (Nixon, Dey, & Davies, 2010), municipal solid waste management (Thampi & Rao, 2012)), • policy making (solar energy technologies utilization (Elkarmi & Mustafa, 1993), energy conservation utilization (Kablan, 2004)), • production planning ( integrated production planning considering manufacturing partners (Jung, 2011), total productive maintenance justification (Kodali & Chandra, 2001), push, pull and hybrid push-pull systems classification (Razmi, Rahnejat, & Khan, 2005)), and…”

Section: Stage 1: Identification Of Extraction Alternatives For Medic...mentioning

confidence: 99%

Application of Ahp Tool for Decision Making of Choice of Technology for Extraction of Anti-Cancer Bioactive Compounds of Plant Origin

Jain

Rao

2013

IJAHP

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Demand for medicinal plants and their exploitation around the world has prompted international agencies like the World Health Organization (WHO) and national health departments like AYUSH to focus on their sustainable utilization. However, lack of any decision-making methodology makes it difficult for the rural entrepreneur to setup a business. This paper has developed a Multi-Criteria Decision Making template, using the Analytic Hierarchy Process (AHP), of ranking the best technology for extraction of nine medicinal plants which grow in Western Ghats of India. These plants have more than 20% subsidy in cultivation under NMMP and have an anticancer property. The technologies selected for AHP were agitation/centrifugation, cold solvent extraction, reflux/soxhlet extraction, cold percolation, microwave assisted extraction, sonication and hot solvent extraction. The ability of the tool to provide selection of the extraction technology with process flexibility like criteria selection, technology selection and criteria weightages allows its use by rural entrepreneurs, technology facilitators, rural entrepreneur proposal evaluators and policy makers.

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“…AHP works its best for decision‐making process in a group of people having consensus. Many authors used AHP in the decision‐making process (e.g., Kablan, (); Herath, (); Randall et al, (); Bascetin, (); Brent, Rogers, Ramabitsa‐Siimane, & Rohwer, (); Iwanejko, (); Wu, Lin, & Chen, (); Srdjevic, (); Contreras, Hanaki, Aramaki, & Connors, (); Dabaghian, Hashemi, Ebadi, & Maknoon, (); Ercanoglu, Kasmer, & Temiz, (); Thapa & Murayama, (); Chatzimouraddis & Pilavachi, (); Chen, ()). Current work on AHP is by Zaidan et al ().…”

Section: Introductionmentioning

confidence: 99%

Trade-off ranking method for multi-criteria decision analysis

Jaini

Utyuzhnikov

2016

J. Multi-Crit. Decis. Anal.

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Multi-criteria decision analysis presumes trade-off between different criteria. As a result, the optimal solution is not unique and can be represented by the Pareto frontier in the objective space.Each Pareto solution is a compromise between different objectives. Despite a limited number of Pareto optimal solutions, the decision-maker eventually has to choose only one option. Such a choice has to be made with the use of additional preferences not included in the original formulation of the optimization problem. The paper represents a new approach to an automatic ranking that can help the decision-maker. In contrast to the other methodologies, the proposed method is based on the minimization of trade-off between different Pareto solutions. To be realized, the approach presumes the existence of a well-distributed Pareto set representing the entire Pareto frontier. In the paper, such a set is generated with the use of the directed search domain algorithm.The method is applied to a number of test cases and compared against two existing alternative approaches. KEYWORDSdirected search domain algorithm, multi-criteria decision analysis, multi-objective optimization, Pareto optimal solution, trade-off, ranking INTRODUCTIONIn the real-life design, it is required to improve different objectives simultaneously. A trade-off between the objectives is usually unavoidable because of the constraints. As a result, the optimal solution is not unique and corresponds to a so-called Pareto solution. In the objective space, all Pareto solutions create a Pareto frontier. For a practical decision-making analysis, the Pareto frontier is represented by a Pareto set that contains a finite number of optimal solutions. Eventually, the decision-maker has to choose only one solution. This leads to the problem of ranking because the formal definition of the Pareto solution does not presume any preferences. An additional algorithm is required to introduce the ranking.In the multi-criteria decision analysis, the ranking problem has been developed for the last 20 years. However, there are no universal approaches. Each method stands on its own background and principles.The most natural approach is to introduce individual preferences. One of the basic and simplest multi-criteria decision analysis techniques is the sum of weightage calculation model. In this technique, a weight is assigned to each criterion to denote its importance. Each aggregate function is then calculated as the sum of weightage criteria. A classic work on the weight determination is by Eckenrode (1965). Eckenrode worked with 24 expert judges, who were required to put a weightage on six criteria in a specified experiment related to an air-defence system.Another well-known decision-making method is the analytic hierarchy process (AHP). AHP was proposed by Saaty (1980). The essence of this method is that human judgement is used in performing evaluations. AHP structures a decision problem into a hierarchy with the goal, decision criteria, and alternatives. Then, it uses the pairwise ...

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The best available technology for small electroplating plants applying analytical hierarchy process

Cited by 11 publications

References 22 publications

Decision Models for the Ranking of Agricultural Water Demand Management Strategies in an Arid Region

Decision Models for the Ranking of Agricultural Water Demand Management Strategies in an Arid Region

Application of Ahp Tool for Decision Making of Choice of Technology for Extraction of Anti-Cancer Bioactive Compounds of Plant Origin

Trade-off ranking method for multi-criteria decision analysis

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