A novel Aczel-Alsina triangular norm-based group decision-making approach under dual hesitant q-rung orthopair fuzzy context for parcel lockers’ location selection

Abstract

For complex last mile problems, the parcel lockers play an important role in urban areas. So, selecting a suitable location is very much crucial to provide optimal service and better logistical performance. From that viewpoint, a multicriteria group decision making method is developed in this article using dual hesitant q-rung orthopair fuzzy (DHq-ROF) set which is more effective than existing variations of fuzzy sets. The Aczel-Alsina (AA) class of t-conorms and t-norms (AAt-CNs&t-Ns) emerged as an important class of union and intersection operations due to its greater flexibility in the information fusion process. To take advantage of the benefits of AAt-CNs&t-Ns and hybrid aggregation operators in DHq-ROF environments, several fundamental operations based on AAt-CNs&t-Ns are first defined. Following the introduction of these stated operations, a series of aggregation operators, viz., DHq-ROF AA weighted averaging, ordered weighted averaging, hybrid averaging and their geometric versions with DHq-ROF information, has been proposed. Based on these operators, a creative approach to handle multi-attribute group decision-making problems has been framed. The parcel lockers’ location selection problem is estimated to validate the created strategy and show its applicability and efficacy. The achieved results establish that the post office is the best location for locating parcel lockers.