AN OPTIMIZATION MODEL FOR EXPLORING THE EGYPTIAN ROYAL PYRAMIDS LOCATIONS

Authors

  • Bahaa Nofal Archaeological Information Systems Program, Faculty of Archaeology, Cairo University, Egypt
  • Assem Tharwat College of Business Administration, American University in the Emirates, UAE
  • Ola El-Aguizy Egyptology Department, Faculty of Archaeology, Cairo University, Egypt
  • Ihab El Khodary Operations Research Department, Faculty of Computers and Artificial Intelligence, Cairo University, Egypt

Keywords:

Egyptian Royal Pyramids, Linear relationships, Mathematical model, RPL theorem, Zero-One Implicit Enumeration

Abstract

The specification of the factor used by the ancient Egyptians to locate their royal pyramids has been an age-old great interest of many archaeologists, some of them concluded that the reason behind the locating of the ancient royal pyramids over such a large territory may never been deduced. This article proposes a new theorem entitled "Royal Pyramids Linearity" (RPL) to introduce a common factor between the majorities of the ancient royal pyramids’ locations in Egypt. The theorem is developed based on an assumption of the existence of linear connections between the ancient locations of some pyramids in Giza, Abusir, Saqqara and Dahshur. The theorem is proved mathematically through the construction of an optimization model that combined hypothesis testing and regression analysis. The model examined 43 royal pyramids. The results emphasized the existence of mathematical linear relationships of 34 that represent all the known royal pyramids constructed starting from the first true pyramid of King Senefru at the fourth dynasty till the last constructed pyramid at the eighteenth dynasty for King Ahmose excluding Khufu and Khafre pyramids. The theorem gives new explanations for the selection of Shepseskaf tomb and the pyramids of Userkaf, Sahure and Khentkaus. In addition, it provides new advantages for the locations of the tomb of Mentuhotep II and the pyramid of Khendjer.

Downloads

Published

2023-07-28

Issue

Section

Articles