Robot selection by a multiple criteria complex proportional assessment method under an interval-valued fuzzy environment

Vahdani, Behnam; Mousavi, Seyed Meysam; Tavakkoli–Moghaddam, Reza; Ghodratnama, Ali; Mohammadi, Mehrdad

doi:10.1007/s00170-014-5849-9

Cited by 61 publications

(27 citation statements)

References 42 publications

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“…Keshavarz Ghorabaee developed a new model by integrating type 2 fuzzy sets and VIKOR method to manage robot evaluation and selection problems. Vahdani et al integrated interval‐valued fuzzy sets and complex proportional assessment (COPRAS) method to select the optimal robot among alternatives. Sen et al applied the preference ranking method for enrichment evaluation (PROMETHEE) II method to assist an industrial company to choose the best‐suited robot.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To reveal the accuracy of the proposed integrated MCDM model for robot selection, we conduct a comparative study with some existing robot selection methods, including the interval‐valued fuzzy VIKOR (IVF‐VIKOR), the interval 2‐tuple linguistic TOPSIS (ITL‐TOPSIS), and the interval‐valued intuitionistic fuzzy COPRAS (IVIF‐COPRAS) . The rankings of the three robots based on the four listed methods are shown in Table .…”

Section: Illustrative Examplementioning

confidence: 99%

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An integrated MCDM method for robot selection under interval‐valued Pythagorean uncertain linguistic environment

et al. 2018

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Robots have received considerable attention in many manufacturing companies due to their great capabilities and characteristics. Selecting an appropriate robot for a specific application can be regarded as a challenging multicriteria decision‐making problem. Furthermore, decision makers are inclined to represent their opinions by using linguistic terms owing to their ambiguous thinking. In this regard, we put forward a novel robot selection model by integrating quality function development (QFD) theory and qualitative flexible multiple criteria method (QUALIFLEX) under interval‐valued Pythagorean uncertain linguistic context. For the developed model, the evaluations given by decision makers are presented as interval‐valued Pythagorean uncertain linguistic sets for dealing with the uncertainty and vagueness of decision makers’ information. An extended QFD method is used for determining criteria weights from the perspective of customers. A modified QUALIFLEX technique based on closeness degree is utilized to generate the ranking order of alternative robots and determine the most suitable one. Finally, an empirical example of an auto manufacturing company is applied to clarify the effectiveness and accuracy of the proposed robot selection approach.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Illustrative Examplementioning

confidence: 99%

An integrated MCDM method for robot selection under interval‐valued Pythagorean uncertain linguistic environment

et al. 2018

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“…In fact, it has been implemented by different companies in the various industries, in which their processes and structures are related to safety of the operations. In addition, the safety management has been applied in a number of industry sectors such as civil aviation [1][2][3], maritime industry [4,5], railway industry [6,7], manufacturing industry [8][9][10] and construction projects [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry

et al. 2017

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In recent years, the implementation of safety management has been increased in construction projects by institutions, and many companies have recognized environmental and social effects of injuries at project work systems. In this regard, a novel decision model is presented based on a new version of complex proportional assessment method with last aggregation under a hesitant fuzzy environment. The decision makers (DMs) assign their opinions by hesitant linguistic variables that are converted to the hesitant fuzzy elements. Also, the DMs' judgments are aggregated in last step of decision making to decrease information loss. Since weights of the DMs or professional safety experts and evaluation criteria are not equal in practice, a new version of hesitant fuzzy compromise solution method is proposed to compute these weights. In addition, the criteria weights are determined based on proposed hesitant fuzzy entropy method. A real case study in developing countries about the safety of construction projects is considered to indicate the suitability and applicability of the proposed new hesitant fuzzy decision model with last aggregation approach. In addition, an illustrative example is prepared to show that the proposed approach is suitable and reliable in larger size safety problems.

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“…Efforts to represent preferences in machine agents have tended to follow in the latter tradition in that they have commonly been inferred from what are assumed to be behavioral correlates of internal states of human agents (e.g., [49]). In other applications, preferences have been defined in the forms of indifference isoquants [94], inferred from choice over a limited set of alternatives [33] or agent designations of importance weights of attributes of alternatives [82].…”

Section: Introductionmentioning

confidence: 99%

Restricted Intervals in Preference Dynamics: Theory and Application in an Agent-Based System

Silver¹,

Rašeta

2015

IEEE Trans. Syst. Man Cybern, Syst.

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Agent-based models have long been used to generate states of variables at individual and aggregate levels. More recently, robotic and computer agents are being given forms in which internal dispositions such as cognitive reasoning, emotions, and preferences are represented. We note limitations in most common representations of preferences in these applications and propose conditions for dynamic forms of the variable. A consequence of the dynamics we propose is that preferences exhibit continuous variation in restricted intervals while maintaining characteristic differences between entities and over time. After giving a form to preferences in a situated application to a consumption system, analytical and computational methods are used to establish that dynamics in the system have properties we describe. We then derive dependencies of the restricted intervals in which preferences typically vary. Estimation of these intervals is exemplified in data on the U.S. economy. The system is then embodied in a network form in which cycle and randomness from environments and their interactions are represented. A demonstration of stochastic resonance in the networked system supports the imputed dynamics. The network model is also used to indicate network dependencies of the bounds of the interval in which preferences vary. Finally, the relevance of the dynamics that are proposed in preferences to other internal dispositions that include emotion in agent-based models is discussed.Index Terms-Agent-based models, autonomous agents, computational network, economic and social agents, networked agents, preference dynamics, stochastic resonance.

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Robot selection by a multiple criteria complex proportional assessment method under an interval-valued fuzzy environment

Cited by 61 publications

References 42 publications

An integrated MCDM method for robot selection under interval‐valued Pythagorean uncertain linguistic environment

An integrated MCDM method for robot selection under interval‐valued Pythagorean uncertain linguistic environment

Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry

Restricted Intervals in Preference Dynamics: Theory and Application in an Agent-Based System

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