In this paper, we extend the concepts of demand data aggregation error to location problems involving coverage. These errors, which arise flora losses in locational information, may lead to suboptimal location patterns. They are potentially more significant in covering problems than in p-median problernsIbecause the distance metric is binary in covering problems. We examine the Hillsirtan and R...

Influence maximization aims at identifying a limited set of key individuals in (social) network which spreads information based on some propagation model and maximizes the number reached. We show that influence probabilistic independent cascade can be modeled as stochastic maximal covering location problem. A reformulation Benders decomposition is proposed relation between obtained optimality c...

Location problems have been the focus of considerable attention both in research and practice for many years. Numerous extensions have been described to broaden its appeal and enhance its applicability. This study proposes a spreadsheet approach for three well-known facility location problems, the p-median problem (PMP), capacitated p-median (CPMP), and maximal covering location problem (MCLP)....

Received Feb 14, 2017 Revised May 30, 2017 Accepted Aug 11, 2017 Ambulance location is one of the critical factors that determine the efficiency of emergency medical services delivery. Maximal Covering Location Problem is one of the widely used ambulance location models. However, its coverage function is considered unrealistic because of its ability to abruptly change from fully covered to unco...

Covering models have found many applications in a wide variety of real-world problems; nevertheless, some assumptions of covering models are not realistic enough. Accordingly, a general approach would not be able to answer the needs of encountering varied aspects of real-world considerations. Assumptions like the unavailability of servers, uncertainty, and evaluating more factors at the same ti...