A grey ordinal priority approach for healthcare waste disposal location selection

Abstract

PurposeIncreasing public consciousness and demand for sustainable environment make selection of a safe location for effective disposal of healthcare waste (HCW) a challenging issue. This problem becomes more complicated due to involvement of multiple decision makers having varying knowledge and interest, conflicting quantitative and qualitative evaluation criteria, and presence of several alternative locations.Design/methodology/approachTo efficiently resolve the problem, the past researchers have already coupled different multi-criteria decision-making tools with uncertainty models and criteria weight measurement techniques, which are time-consuming and highly computationally complex. Based on involvement of a group of experts expressing their opinions with respect to relative importance of criteria and performance of alternative locations against each criterion, this paper proposes application of ordinal priority approach (OPA) integrated with grey numbers to solve an HCW disposal location selection problem.FindingsThe grey OPA can simultaneously estimate weights of the experts, criteria and locations relieving the decision makers from complicated computational steps. The potentiality of grey OPA in solving an HCW disposal location selection problem is demonstrated here using an illustrative example consisting of three experts, six criteria and four alternative locations.Originality/valueThe derived results show that it can be employed to deal with real-time HCW disposal location selection problems in uncertain environment providing acceptable and robust decisions. It relieves the experts from pair-wise comparisons of criteria, normalization of data, identification of ideal and anti-ideal solutions, aggregation of information and so on, while arriving at the most consistent decision with minimum computational effort.

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“…From methodological aspects, OPA-G can be expanded and applied innovatively to solve complex decision-making problems in any industry. Chakraborty et al, 2023 employed OPA-G for selecting the safe locations to dispose of healthcare waste. The outputs of OPA-G address the demand for a sustainable environment and public consciousness.…”

Utilizing a Fractional-Order Grey Model to Predict the Development Trends of China’s Electronic Commerce Service Industry

“…This theory provides a feasible solution for analysis and decisionmaking problems under the condition of small data sets and is widely used in different application fields, such as engineering, manufacturing, business, etc. [7][8][9][10][11][12][13]. Grey modeling is an important branch of grey system theory and is mainly used for the extraction of pattern trends from small data sets [14].…”