CO2 pollution reduction: a tradeoff for fully fuzzy parameters in a megaproject optimization

Abstract

PurposeThis paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO2 tradeoff problem (FDTCQRP*TP) in a megaproject based on fuzzy ground.Design/methodology/approachA combinatorial evolutionary algorithm using Fuzzy Invasive Weed Optimization (FIWO) is used in the discrete form of the problem where the parameters are fully fuzzy multi-objective and provide a space incorporating all dimensions of the problem. Also, the fuzzy data and computations are used with the Chanas method selected for the computational analysis. Moreover, uncertainty is defined in FIWO. The presented FIWO simulation, its utility and superiority are tested on sample problems.FindingsThe reproduction, rearrangement and maintaining elite invasive weeds in FIWO can lead to a higher level of accuracy, convergence and strength for solving FDTCQRP*TP fuzzy rules and a risk ground in the ambiguous mode with the emphasis on the necessity of CO2 pollution reduction. The results reveal the effectiveness of the algorithm and its flexibility in the megaproject managers' decision making, convergence and accuracy regarding CO2 pollution reduction.Originality/valueThis paper offers a multi-objective fully fuzzy tradeoff in the ambiguous mode with the approach of CO2 pollution reduction.