Household solid waste processing plant location selection: interval-valued intuitionistic fuzzy information-based gained and lost dominance score approach

Household solid waste (HSW) poses long-term environmental and human health-related risks as it contains several toxic components. In the recent past, most of the developing countries strive to improve their urban HSW management practices globally. The management capability or incapability of HSW processing plant (HSWPP) depends on its location. The location selection for HSWPP is a complex multi-criteria decision analysis problem for the policymakers in developing nations. Uncertainty is more common in the selection of HSWPP location from multiple criteria perspective. This paper aims to develop a decision-making method for assessing and choosing a suitable HSWPP location under the context of interval-valued intuitionistic fuzzy sets (IVIFSs). As a generalized form of fuzzy set, IVIFS theory has been demonstrated as a valuable way for measuring the uncertainty of information in realistic decision-making problems. In IVIFS, the membership grades of an object are subsets of closed interval [0, 1], therefore, the theory of IVIFS is more useful to present the opinions in terms of intervals instead of the crisp numbers. This paper firstly proposes a novel distance measure for IVIFSs to estimate dissimilarity value between IVIFSs. Few pairs of IVIFSs are taken to demonstrate the advantage of proposed distance measure over extant measures. Next, this study develops a new IVIF-score function by analyzing the drawbacks of extant interval-valued intuitionistic fuzzy (IVIF)-score and accuracy functions. Further, the proposed score function is used to determine the significance values of involved decision makers. In this approach, the objective weight of criteria is derived through IVIF-standard deviation-based approach and subjective weight of criteria is obtained with IVIF-pivot pairwise relative criteria importance assessment (PIPRECIA) approach and finally, a collective weighting formula is discussed with combination of objective and subjective weights of criteria. Finally, a hybrid gained and lost dominance score (GLDS) method is developed to solve the decision-making problems on IVIFSs setting. Further, we discuss an empirical study of HSWPP locations assessment problem to show the reasonableness and exhibit the efficacy of the presented approach. Moreover, we discuss sensitivity assessment over various values of a parameter, which proves the stability of obtained outcomes. Comparison with extant methods is made to illustrate the robustness of proposed framework. The present work offers a new methodology, which can help the policymakers to evaluate HSWPP locations with uncertain information.