Prioritizing sustainable electricity production technologies: MCDM approach

Štreimikienė, Dalia; Baležentis, Tomas; Kriščiukaitienė, Irena; Baležentis, Аlvydas

doi:10.1016/j.rser.2012.02.067

Cited by 248 publications

(105 citation statements)

References 24 publications

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“…Brauers andZavadskas (2010, 2011) suggested that if any of the xij value is 0, which signifies the absence of a particular criterion in the decision matrix, a foregoing filtering stage or withdrawal of that criterion from the decision matrix can be considered. MULTIMOORA method has been applied for personnel selection Balezentis and Zeng, 2013), energy management (Streimikiene et al, 2012;Balezentiene et al, 2013) and property selection (Brauers & Zavadskas, 2011).…”

Section: Full Multiplicative Formmentioning

confidence: 99%

A study on the ranking performance of some MCDM methods for industrial robot selection problems

Karande¹,

Zavadskas²,

Chakraborty³

2016

10.5267/j.ijiec

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In this paper, the ranking performance of six most popular and easily comprehensive multicriteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.

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Section: Full Multiplicative Formmentioning

confidence: 99%

A study on the ranking performance of some MCDM methods for industrial robot selection problems

Karande¹,

Zavadskas²,

Chakraborty³

2016

10.5267/j.ijiec

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“…Standard decision-making matrix is provided as follows (Eq .9) (9) Rij represents normalised matrix.In this stage, different normalization techniques can be used.…”

Section: Standard Decision Matrixmentioning

confidence: 99%

“…When the studies in literature are investigated, MCDM techniques are grouped under 15 topics: Energyenvironment-sustainability, supply chain management, material, quality management, Geographic Information Systems (GIS), construction and project management, safety and risk management, manufacturing systems, technology management, operation research and soft computing, strategic management, knowledge management, production management, tourism management and the other fields [2]. For MCDM techniques, there are a lot of studies in the area of material science [3][4][5][6][7][8], production technologies [9], mass production [10], infrastructures [11], manufacturing systems [12], global production [13] and production strategies [14]. There is a large volume of published studies in MCDM for manufacturing and material science.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

Sofuoğlu

Orak

2017

ijisae

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Abstract:Multi criteria decision making models (MCDM) are extensively used in material and process selection in engineering. In this study, a novel hybrid decision making model is developed. Best-Worst method (BWM) is hybridized with TOPSIS, Grey Relational Analysis (GRA) and Weighted Sum Approach (WSA). Developed hybrid models produce similar results in different weight value of decision makers so they are combined. The model is tested in a turning operation and an optimization study is conducted by using Taguchi experimental design. The developed model can be used by engineers and operators in manufacturing environment.

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“…There has been an increasing amount of literature on multi criteria decision making models (MCDM). There are a lot of studies in the area of material science [15][16][17][18][19][20], production technologies [21], mass production [22], manufacturing sector [23], manufacturing systems [24], global production [25] and production strategies [26]. There are a lot of published studies in MCDM for manufacturing and material science.…”

Section: Introductionmentioning

confidence: 99%

Hybridizing a Multi Response Taguchi Algorithm with Reference Ideal Method to Solve Machining Problems

Sofuoğlu¹

2017

ijisae

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New materials lead to the occurrence of high technology industries. These materials are high strength, corrosion and heat resistant steel alloys, titanium, ceramics, composites, and other non-metallic materials. Conventional machining methods are not proper to machine these materials in terms of high surface quality. Such materials are generally processed using non-traditional machining methods. Multi criteria decision making models (MCDM) are extensively used in material-process selection, and optimization of machining problems in engineering. In this study, a novel hybrid optimization model is proposed. Taguchi method is hybridized with Reference Ideal Method. The model is tested using two case studies (conventional and non-traditional machining problems) taken from literature. The proposed model can be used by engineers and operators in manufacturing environment.

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Prioritizing sustainable electricity production technologies: MCDM approach

Cited by 248 publications

References 24 publications

A study on the ranking performance of some MCDM methods for industrial robot selection problems

A study on the ranking performance of some MCDM methods for industrial robot selection problems

A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

Hybridizing a Multi Response Taguchi Algorithm with Reference Ideal Method to Solve Machining Problems

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