en پژوهشي Research <span style="FONT-SIZE: 15pt FONT-FAMILY: 'Rockwell Extra Bold' mso-fareast-font-family: 'Times New Roman' mso-ansi-language: EN-US mso-fareast-language: EN-US mso-bidi-language: FA mso-bidi-font-size: 11.0pt mso-bidi-font-family: 'Times New Roman'"><a name="OLE_LINK2"><span style="FONT-SIZE: 11pt FONT-FAMILY: 'Times New Roman' mso-fareast-font-family: 'Times New Roman' mso-ansi-language: EN-US mso-fareast-language: EN-US mso-bidi-language: FA">Capacitated p-median problem (CPMP) is a well-known facility-location problem, in which p capacitated facility points are selected to satisfy n demand points in such a way that the total assigned demand to each facility does not exceed its capacity. Minimizing the total sum of distances between each demand point and its nearest facility point is the objective of the problem. Developing an efficient solution method for the problem has been a challenge during last decades in literature. In this paper, a hybrid met heuristic called GACO is developed to find high quality and fast solutions for the CPMP. The GACO combines elements of genetic algorithm and ant colony optimization met heuristics. Computational results on standard test problems show the robustness and efficiency of the algorithm and confirm that the proposed method is a good choice for solving the CPMP<span style="COLOR: black"><font face="Times New Roman" size="3">.</font></span></span></a></span> Facility location problem, p-median problem, Hybrid metaheuristic, Genetic algorithm, Ant colony optimization 11 15 http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-94-4&slc_lang=en&sid=1 M. Yaghini yaghini@iust.ac.ir 18003194753284600581 18003194753284600581 Yes J. Lessan 18003194753284600653 18003194753284600653 No H. Gholami Mazinan 18003194753284600654 18003194753284600654 No