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Current research on group decision making (GDM) focuses on how to quickly reach a consensus, in which decision makers’ opinions are mainly changed by feedback suggestion, not by changing circumstances over time. In a long-term GDM problem, decision-makers may be affected by the environment to change their views. For example, real estate market prices will affect residents’ opinions in time-consuming demolition negotiations. We introduce time uncertainty to study the long-term GDM problem with random opinions following this idea. This article constructs the minimum cost and maximum utility-based consensus models in GDM with random opinion based on the time uncertainty. The optimal time of decision-making can be determined. Specifically, the real options theory is employed to study time uncertainty. Furthermore, the feasibility of the models is verified by case analysis of China’s demolition negotiation for old communities’ renewal projects, and sensitivity analyses are developed to analyse the robustness of our models. In the case analysis and sensitivity analysis, we obtain the optimal solution of models by using a genetic algorithm based on MATLABR2018b.

Time uncertainty and random opinion based group decision making for demolition negotiations