A hybrid multi-criteria decision-making model for optimal coal blending

2019 ◽  
Vol 14 (2) ◽  
pp. 339-359 ◽  
Author(s):  
Shankar Chakraborty ◽  
Ankan Mitra
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Research Work ◽  
Carbon Dioxide Emission ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Geographical Regions ◽  
Coal Blending ◽  
Decision Making Model

Purpose The purpose of this paper is thus to develop a hybrid decision-making model for optimal coal blending strategy. Coal is one of the major resources contributing to generation of electricity and anthropogenic carbon-dioxide emission. Being formed from dead plant matter, it undergoes a series of morphological changes from peat to lignite, and finally to anthracite. Because of non-uniform distribution of coal over the whole earth and continuous variation in its compositions, coals mined from different parts of the world have widely varying properties. Hence, it requires an ideal blending strategy such that the coking coal having the optimal combination of all of its properties can be used for maximum benefit to the steel making process. Design/methodology/approach In this paper, a multi-criteria decision-making approach is proposed while integrating preference ranking organization method for enrichment of evaluations (PROMETHEE II and V) and geometrical analysis for interactive aid (GAIA) method to aid in formulating an optimal coal blending strategy. The optimal decision is arrived at while taking into account some practical implications associated with blending of coal, such as coal price from different reserves. Findings Different grades of coal are ranked from the best to the worst to find out the composition of constituent coals in the final blending process. Coals from the mines of two different geographical regions are considered here so as to prove the applicability of the proposed model. Adoption of this hybrid decision-making model would subsequently improve the performance of coal after blending and help in addressing some sustainability issues, like less pollution. Originality/value As this model takes into account the purchase price of coals from different reserves, it is always expected to provide more realistic solutions. Thus, it would be beneficial to deploy this decision-making model to different blending optimization problems in other spheres of a manufacturing industry. This model can further accommodate some more realistic criteria, such as availability of coal in different reserves as a topic of future research work.

Evaluation of energy sources based on sustainability factors using integrated fuzzy MCDM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santosh K. Saraswat ◽  
Abhijeet K. Digalwar
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Economic Benefits ◽  
Decision Makers ◽  
Preference Ranking ◽  
Energy Sources ◽  
Content Type ◽  
Weighted Sum Method ◽  
Weight Calculation ◽  
Social Environmental

Purpose The purpose of this paper is to develop an integrated fuzzy multi-criteria decision-making (MCDM) model for evaluation of the energy alternates in India based on their sustainability. Design/methodology/approach A fuzzy analytical hierarchy process approach is used for the weight calculation of the criteria and the fuzzy technique for order preference by similarity to the ideal solution is used for ranking of the energy alternates. Seven energy sources – thermal, gas power, nuclear, solar, wind, biomass and hydro energy are considered for the assessment purpose on the basis of sustainability criteria, namely, economic, technical, social, environmental, political and flexible. Findings The result of the analysis shows that economics is the highest weight criterion, followed by environmental and technical criteria. Solar energy was chosen as the most sustainable energy alternate in India, followed by wind and hydro energy. Research limitations/implications Few other MCDM techniques such as VIseKriterijumska Optimizacija I Kompromisno Resenje (multi-criteria optimization and compromise solution), weighted sum method and preference ranking organization method for enrichment evaluations – II can also be explored for the sustainability ranking of the energy alternates. However, the present model has also provided a good result. Practical implications The present research work will help the decision-makers and organizations in the evaluation and prioritizing the various energy sources on the scale of sustainability. Social implications Research finding provides guidance to government and decision-makers regarding the development of social conditions through energy security, job creation and economic benefits. Originality/value Research work can be act as a supplement for the investors and decision-makers specifically in prioritizing the investment perspective and to support other multi-perspective decision-making problems.

An integrated fuzzy-based multi-criteria decision-making approach for the selection of an effective manufacturing system

2018 ◽  
Vol 25 (1) ◽  
pp. 280-296 ◽  
Author(s):  
Ram Prakash ◽  
Sandeep Singhal ◽  
Ashish Agarwal
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Sustainable Growth ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Manufacturing Company ◽  
Selection Of

Purpose The research paper presents analysis and prioritization of barriers influencing the improvement in the effectiveness of manufacturing system. The purpose of this paper is to develop an integrated fuzzy-based multi-criteria decision-making (F-MCDM) framework to assist management of the case company in the selection of most effective manufacturing system. The framework helps in prioritizing the manufacturing systems on the basis of their effectiveness affected by the barriers. Design/methodology/approach In this paper, on the basis of experts’ opinion, five barriers have been identified in a brain-storming session. The problem of prioritization of manufacturing system is a multi-criteria decision-making (MCDM) problem and hence is solved by using the F-MCDM approach using dominance matrix. Findings Manufacturing systems’ effectiveness for Indian industries is influenced by barriers. The prioritization of manufacturing systems depends on qualitative factor decision-making criteria. Among the manufacturing systems, leagile manufacturing system is given the highest priority followed by lean manufacturing system, agile manufacturing system, flexible manufacturing system and cellular manufacturing system. Research limitations/implications The selection of an appropriate manufacturing system plays a vital role for sustainable growth of the manufacturing company. In the present work, barriers which influence the effectiveness of manufacturing system have been identified. On the basis of degree of influence of barriers on the effectiveness of the manufacturing system, five alternative manufacturing systems are prioritized. The framework will help the management of the case company to take reasonable decision for the adoption of the appropriate manufacturing system. Practical implications The results of the research work are very useful for the manufacturing companies interested in analyzing the alternative manufacturing systems on the basis of their effectiveness and their sensitivity toward various barriers. The management of Indian manufacturing company will take decision to adopt a manufacturing system whose effectiveness is least sensitive toward barriers. Effectiveness of such manufacturing system will improve with time without having retardation due to barriers. With improved effectiveness of the manufacturing system, the manufacturing company would be able to survive with global competition. The result of the present work is based on the inputs from the case company and may vary for the other manufacturing company. In the present work, only five alternative manufacturing systems and five barriers have been considered. To obtain the better result, MCDM approach with more number of alternative manufacturing systems and barriers might be considered. Originality/value The research work is based on the fuzzy analytic hierarchy process framework and on the case study conducted by the authors. The work carried out is original in nature and based on the real-life case study.

A multi-criteria decision making model for outsourcing maintenance services

Facilities ◽  
2015 ◽  
Vol 33 (3/4) ◽  
pp. 229-244 ◽  
Author(s):  
Mohammad A. Hassanain ◽  
Sadi Assaf ◽  
Abdul-Mohsen Al-Hammad ◽  
Ahmed Al-Nehmi
Keyword(s):  
Decision Making ◽  
Air Conditioning ◽  
Relative Weight ◽  
Equal Weight ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Air Conditioning Systems ◽  
Decision Making Model ◽  
Outsourcing Decision

Purpose – The purpose of this paper is to present the development of a multi-criteria decision-making model for use by maintenance managers to consider before making a decision on outsourcing. Design/methodology/approach – Thirty-eight factors were identified for outsourcing maintenance services. These factors were grouped under six categories, namely: “strategic”, “management”, “technological”, “quality”, “economic” and “function characteristics”. The Analytic Hierarchy Process, as a multi-criteria decision-making model, was introduced and applied as an approach for maintenance managers in Saudi Arabian universities to consider before making a decision on outsourcing. A case study on the outsourcing decision of maintenance services of air-conditioning systems was carried out to apply the developed model. Findings – Data analysis indicated that all outsourcing decision groups of factors have almost equal weight, with the “quality” group of factors having the highest weight and the “technological” group of factors having the least weight. Further, the analysis indicated, in general, that the recommended decision for the maintenance managers is to outsource. However, an application of the developed model through a case study on the outsourcing of maintenance services of air-conditioning systems showed that the recommended action is not to outsource. Originality/value – The presented approach in this paper could be of practical benefit to maintenance managers in their decision making of whether or not to outsource maintenance services. The factors in the model were identified through a literature survey of research carried out in different countries. Therefore, the model could be applied in different settings, depending on the relative weight of the factors by the users.

Modeling enablers of knowledge management process using multi criteria decision making approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishant Agrawal
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Research Work ◽  
Research Area ◽  
Multi Criteria Decision Making ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Effect Relationship ◽  
Integrated Method ◽  
Knowledge Based

Purpose Drawing from boundary-spamming knowledge processes and knowledge-based theory, the purpose of this paper is to study enablers of the knowledge management (KM) process using robust multi-criteria decision-making (MCDM) tools like interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method. Design/methodology/approach Drawing on the knowledge-based view and through the detailed literature review among different KM success, eight enablers were identified. By using the ISM-DEMATEL approach, a systematic framework was designed, and further cause–effect relationship diagram visualized a causal relationship among the enablers. Findings The combined approach of ISM-DEMATEL showcase that “knowledge creation” and “knowledge capture” are essential enablers. These two identified enablers have considered being pillars for KM implementation. On the other side, knowledge organization, knowledge application are dependent enablers. Practical implications From a practical viewpoint, the findings of this research work enable the industry consultants to identify the most prominent driving enablers for KM implementation. Additionally, it provides a clue for the effective implementation of KM in a systematic approach. Originality/value The integrated method depending on the hierarchical model and cause–effect relationship between enablers of the KM process is a novel approach that opens a new research area in this domain. Moreover, this is the first-ever attempt to combine ISM along with DEMATEL to identify enablers of the KM process.

Multi-criteria decision making towards selection of industrial robot

2015 ◽  
Vol 22 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Saroj Kumar Patel ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Making ◽  
Selection Problem ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Promethee Ii ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Robot Selection ◽  
Selection Of

Purpose – Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method. Design/methodology/approach – Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making. Findings – In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches. Originality/value – The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.

Measuring the supply chain competitiveness of e-commerce industry in Indonesia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ade Febransyah ◽  
Joklan Imelda Camelia Goni
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
The Future ◽  
Business To Consumer ◽  
Software And Hardware ◽  
Decision Making Model

Purpose The purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia. Design/methodology/approach The study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure. Findings The findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware. Research limitations/implications In this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice. Practical implications With this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player. Originality/value E-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

scholarly journals Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Multinational Enterprises ◽  
Value Added ◽  
Plant Performance ◽  
Multi Criteria Decision Making ◽  
African Countries ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Decision Making Model

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.

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