Discrete Optimization Efficient scheduling of periodic information monitoring requests Daniel D. Zeng, Moshe Dror * , Hsinchun Chen Department of Management Information Systems, Eller College of Management, University of Arizona, 1130 E. Helen Street, Tucson, Arizona 85721, USA Received 23 June 2003; accepted 28 January 2005 Available online 14 April 2005 Abstract In many mission-critical applications such as police and homeland security-related information systems, automated monitoring of relevant information sources is essential. Such monitoring results in a large number of periodic queries, which can significantly increase the load on a server that hosts information services. If the execution of these queries is not carefully scheduled on the server, high peak load might occur, leading to degraded service quality. We investigate this query scheduling problem with the objective of minimizing the serverÕs peak load. We state an optimization-based formulation and show that this problem is NP-hard in the strong sense. Subsequently, several greedy heuristic approaches are developed and compared via a computational study with respect to solution quality and computational efficiency. Ó 2005 Elsevier B.V. All rights reserved. Keywords: Scheduling; Greedy heuristics; Periodic queries 1. Introduction In many applications, it is critical to monitor on an ongoing basis a given set of information sources for changes. For instance, this is the case in police investigations. Crime analysts and detectives re- quest information on developments and updates concerning targeted suspects and stolen vehicles (Chen et al., 2003). Similar periodic requests arise in many other application settings, e.g., when poll- ing signals from avionics equipment connected to a communication bus (Sundstrom et al., 1978), retrieving financial information from the Internet (Sycara et al., 1998), collecting document meta- information to build a digital library (Bowman et al., 1995; Zagalo et al., 2001), and serving 0377-2217/$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.ejor.2005.01.057 * Corresponding author. Tel.: +1 520 621 4614; fax: +1 520 621 2433. E-mail addresses: zeng@eller.arizona.edu (D.D. Zeng), mdror@eller.arizona.edu (M. Dror), hchen@eller.arizona.edu (H. Chen). European Journal of Operational Research 173 (2006) 583–599 www.elsevier.com/locate/ejor