Extension of TODIM combined with grey numbers: an integrated decision making module

2015 ◽  
Vol 5 (3) ◽  
pp. 367-391 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra

Purpose – Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be subjective or objective (or combination of both), depending upon the situation; requirements may also be conflicting. In practice, most of the real-world decision-making problems are based on subjective evaluation criteria which are basically ill-defined and vague. Since subjective human judgment bears ambiguity and vagueness in the decision making; application of grey numbers set theory may be proved fruitful in this context. The paper aims to discuss these issues. Design/methodology/approach – Owing to the advantages of grey numbers set theory in tackling subjectivity in decision making; the crisp-TODIM needs to be extended by integrating with grey numbers set theory in order to facilitate decision making consisting of subjective data. Hence, the unified objective of this paper is to propose a grey-based TODIM approach in the context of decision making. Findings – Application potential of grey-TODIM has been demonstrated through a case empirical robot selection problem. Result obtained thereof, has also been compared to that of existing grey-based decision support systems available in literature. Originality/value – Application potential of grey-based decision support systems (grey-TOPSIS, grey analysis, grey-MOORA) have been highlighted in available literature resource. However, the shortcoming of these approaches is that they do not consider decision-makers’ risk attitude while decision making. TODIM method is derived from the philosophy of Cumulative Prospect Theory (CPT) which considers risk averting attitude of the decision maker in case of gain and risk seeking attitude in case of loss, while comparing dominance between two alternatives with respect to a particular criterion. Hence, this paper contributes a mathematical foundation of TODIM coupled with grey numbers set theory for logical decision making.

2016 ◽  
Vol 23 (4) ◽  
pp. 983-1014 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
S.S. Mahapatra

Purpose – Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues. Design/methodology/approach – Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data. Findings – An empirical case study has been demonstrated in the context of robot selection problem. Finally, a sensitivity analysis has been performed to make the robot selection process more robust. A trade-off between objective criteria measure and subjective criteria measure has been shown using sensitivity analysis. Originality/value – Robot selection has long been viewed as an important decision-making scenario in the industrial context. Appropriate robot selection helps in enhancing value of the product and thereby, results in increased profitability for the manufacturing industries. The proposed decision support system considering simultaneous exploration of subjective as well as objective database is rarely attempted before.


2015 ◽  
Vol 4 (1) ◽  
pp. 45-66 ◽  
Author(s):  
Patrizia Lombardi ◽  
Valentina Ferretti

Purpose – Policy makers are frequently challenged by the need to achieve sustainable development in cities and regions. Current decision-making processes are based on evaluation support systems which are unable to tackle the problem as they cannot take a holistic approach or a full account of actors. The purpose of this paper is to present a new generation of evaluation systems to support decision making in planning and regeneration processes which involve expert participation. These systems ensure network representation of the issues involved and visualization of multiple scenarios. Design/methodology/approach – A literature review is used for both revising existing evaluation tools in urban planning and the built environment and highlighting the need to give stakeholders (industry, cities, operators, etc.) new tools for collaborative or individual decisions and to facilitate scaling up solutions. An overview of the new generation of decision support systems, named Multicriteria Spatial Decision Support Systems (MC-SDSS) is provided and real case studies are analyzed to show their ability to tackle the problem. Findings – Recent research findings highlight that decisions in urban planning should be supported by collaborative and inclusive processes. Otherwise, they will fail. The case studies illustrated in this study highlight the usefulness of MC-SDSS for the successful resolution of complex problems, thanks to the visualization facilities and a network representation of the scenarios. Research limitations/implications – The case studies are limited to the Italian context. Practical implications – These SDSS are able to empower planners and decision makers to better understand the interaction between city design, social preferences, economic issues and policy incentives. Therefore, they have been employed in several case studies related to territorial planning and regeneration processes. Originality/value – This study provides three case studies and a review of the new MC-SDSS methodology which involve the Analytic Network Process technique to support decision-making in urban and regional planning.


2017 ◽  
Vol 117 (7) ◽  
pp. 1376-1388 ◽  
Author(s):  
Fahham Hasan Qaiser ◽  
Karim Ahmed ◽  
Martin Sykora ◽  
Alok Choudhary ◽  
Mike Simpson

Purpose Decision making in logistics is an increasingly complex task for organizations as these involve decisions at strategic, tactical and operational levels coupled with the triple-bottom line of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. The purpose of this paper is to explore the current state of the research in the domain of DSS for logistics while considering sustainability aspects. Design/methodology/approach A systematic review approach using a set of relevant keywords with several exclusion criteria was adopted to identify literature related to DSS for sustainable logistics. A total of 40 papers were found from 1994 to 2015, which were then analyzed along the dimensions of publishing trend, geographic distribution and collaboration, the most influential journals, affiliations and authors as well as the key themes of identified literature. The analysis was conducted by means of bibliometric and text mapping tools, namely BibExcel, gpsvisualizer and VOSviewer. Findings The bibliometric analysis showed that DSS for sustainable logistics is an emerging field; however, it is still evolving but at a slower pace. Furthermore, most of the contributing affiliations belong to the USA and the UK. The text mining and keyword analysis revealed key themes of identified papers. The inherent key themes were decision models and frameworks to address sustainable logistics issues covering transport, distribution and third-party logistics. The most prominent sustainable logistics issue was carbon footprinting. Social impact has been given less attention in comparison to economic and environmental aspects. The literature has adequate room for proposing more effective solutions by considering various types of multi-criteria decision analysis methods and DSS configurations while simultaneously considering economic, environmental and social aspects of sustainable logistics. Moreover, the field has potential to include logistics from wide application areas including freight transport through road, rail, sea, air as well as inter-modal transport, port operations, material handling and warehousing. Originality/value To the best of the authors’ knowledge, this is the first systematic review of DSS for sustainable logistics using bibliometric and text analysis. The key themes and research gaps identified in this paper will provide a reference point that will encourage and guide interested researchers for future study, thus aiding both theoretical and practical advancements in this discipline.


Author(s):  
Soraya Rahma Hayati ◽  
Mesran Mesran ◽  
Taronisokhi Zebua ◽  
Heri Nurdiyanto ◽  
Khasanah Khasanah

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR


2018 ◽  
Vol 1 (2) ◽  
pp. 45-54
Author(s):  
Helpi Nopriandi

Tenaga Kependidikan merupakan anggota masyarakat yang mengabdikan diri dan diangkat untuk menunjang penyelenggaraan pendidikan. Decision Support Systems atau lebih dikenal dengan Sistem Pendukung Keputusan adalah bagian dari sebuah sistem informasi yang berbasis komputer termasuk sistem yang berbasis ilmu pengetahuan dan dipakai untuk mendukung pengambil  keputusan dalam suatu organisasi atau perusahaan. untuk memudahkan pimpinan dalam mengambil sebuah keputusan dibuatlah suatu sistem pengambil keputusan dengan menggunakan Fuzzy Multiple Attribute Decision Making  (FMADM) digunakan untuk mencari alternatif optimalkan dari sejumlah alternatif dengan kriteria tertentu, sedangkan metode Simple Additive Weighting (SAW). Metode SAW sering juga dikenal istilah metode penjumlahan terbobot. Konsep dasar metode SAW adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif dari semua atribut.


2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality  of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.


Author(s):  
Jitka Janová ◽  
M. Lindnerová

The decision support systems commonly used in industry and economy managerial practice for optimizing the processes are based on algoritmization of the typical decision problems. In Czech forestry business, there is a lack of developed decision support systems, which could be easily used in daily practice. This stems from the fact, that the application of optimization methods is less successful in forestry decision making than in industry or economy due to inherent complexity of the forestry decision problems. There is worldwide ongoing research on optimization models applicable in forestry decision making, but the results are not globally applicable and moreover the cost of possibly arising software tools are indispensable. Especially small and medium forestry companies in Czech Republic can not afford such additional costs, although the results of optimization could positively in­fluen­ce not only the business itself but also the impact of forestry business on the environment. Hence there is a need for user friendly optimization models for forestry decision making in the area of Czech Republic, which could be easily solved in commonly available software, and whose results would be both, realistic and easily applicable in the daily decision making.The aim of this paper is to develop the optimization model for the machinery use planning in Czech logging firm in such a way, that the results can be obtained using MS EXCEL. The goal is to identify the integer number of particular machines which should be outsourced for the next period, when the total cost minimization is required. The linear programming model is designed covering the typical restrictions on available machinery and total volume of trees to be cut and transported. The model offers additional result in the form of optimal employment of particular machines. The solution procedure is described in detail and the results obtained are discussed with respect to its applicability in practical forestry decision making. The possibility of extension of suggested model by including additional requirements is mentioned and the example for the wood manipulation requirement is shown.


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