On Modeling of Sorted Cost Consensus Negotiation Considering Efficiency and Time Based on the Stochastic Programming

Yi Zhou (), Chonglan Guo, Guo Wei and Enrique Herrera-Viedma ()
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Yi Zhou: School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Chonglan Guo: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, The Research Institute for Risk Governance and Emergency DecisionMaking, School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Guo Wei: Department of Mathematics and Computer Science, The University of North Carolina at Pembroke, Pembroke, NC 28372, USA
Enrique Herrera-Viedma: Andalusian Research Institute in Data Science and Computational Intelligence, Department of Computer Science and AI, University of Granada, 18071 Granada, Spain

Mathematics, 2023, vol. 11, issue 2, 1-37

Abstract: In the consensus reaching process (CRP) permitting negotiation, the efficiency of negotiation is affected by the order of negotiation with decision makers (DMs), the time, and the number of moderators. In this paper, the sorted negotiation against DMs considering efficiency and time is initiated into consensus decision making, which can improve the speed and effectiveness of consensus. Based on the opinion dynamics (opinion evolution), uniform and normal distributions are used to describe the uncertainty of DMs’ opinions and negotiation time, the opinion order efficiency and cost coefficient are coined, and the cost-constrained optimal efficiency sorted negotiation model and the optimal efficiency sorted negotiation model involving multiple moderators and time constraints are respectively constructed. The optimal solution of the chance-constrained model is obtained in the context of China’s urban demolition negotiation using an improved genetic algorithm, and an optimum set of influential individuals based on opinion similarity is introduced so that assessment criteria for validating the reasonableness of the sorting sequence are determined. Sorted consensus negotiation combined with complex scenarios such as different representation formats of opinions, characteristics of DMs, other solving algorithms, Bayesian dynamics, etc. can be included in future works.

Keywords: stochastic programming; genetic algorithm; group decisions and negotiations; sorted cost consensus; opinion order efficiency (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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