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Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach

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School of Management, Shanghai University, Shanghai 200444, China
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School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
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School of Economics and Management, Tongji University, Shanghai 200092, China
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Department of Economics & Management, Yibin University, Yibin 644007, China
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Author to whom correspondence should be addressed.
Entropy 2018, 20(5), 349; https://doi.org/10.3390/e20050349
Received: 13 April 2018 / Revised: 2 May 2018 / Accepted: 7 May 2018 / Published: 7 May 2018
(This article belongs to the Section Information Theory, Probability and Statistics)
Nowadays robots have been commonly adopted in various manufacturing industries to improve product quality and productivity. The selection of the best robot to suit a specific production setting is a difficult decision making task for manufacturers because of the increase in complexity and number of robot systems. In this paper, we explore two key issues of robot evaluation and selection: the representation of decision makers’ diversified assessments and the determination of the ranking of available robots. Specifically, a decision support model which utilizes cloud model and TODIM (an acronym in Portuguese of interactive and multiple criteria decision making) method is developed for the purpose of handling robot selection problems with hesitant linguistic information. Besides, we use an entropy-based combination weighting technique to estimate the weights of evaluation criteria. Finally, we illustrate the proposed cloud TODIM approach with a robot selection example for an automobile manufacturer, and further validate its effectiveness and benefits via a comparative analysis. The results show that the proposed robot selection model has some unique advantages, which is more realistic and flexible for robot selection under a complex and uncertain environment. View Full-Text
Keywords: robot selection; cloud model; TODIM method; combination weight; entropy method robot selection; cloud model; TODIM method; combination weight; entropy method
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Wang, J.-J.; Miao, Z.-H.; Cui, F.-B.; Liu, H.-C. Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach. Entropy 2018, 20, 349.

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