Advances in the decision-making of set covering models under uncertainty

The Set Covering Problem (SCP) has been an extensively studied NP-hard problem in the field of combinatorial optimization since 1970. Over the past five decades, a significant amount of research has led to the development of a diverse set of covering models to support decision-making in various areas. However, the SCPs related to real-world applications are often too complex to solve using existing algorithms due to uncertain problem parameters. Thus, given the diversity of new developments, there is a pressing need to know both the current solution approaches and the advanced strategies for studying the uncertain SCP. This study summarizes the various modeling and solution approaches to the SCP when the model parameters are uncertain. Further, this study discusses some promising future research directions of the uncertain SCP that will impact new investigations of decisions on complex and competitive real-world issues.