Research Article OptimumSchedulingtheElectricDistributionSubstationswitha CaseStudy:AnIntegerGaining-SharingKnowledge-Based MetaheuristicAlgorithm SaidAliHassan, 1 KhalidAlnowibet, 2 PrachiAgrawal, 3 andAliWagdyMohamed 4,5 1 Department of Operations Research and Decision Support, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt 2 College of Science, Department of Statistics and Operations Research, King Saud University, Riyadh, Saudi Arabia 3 Department of Mathematics and Scientific Computing, National Institute of Technology Hamirpur, Hamirpur 177005, Himachal Pradesh, India 4 Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt 5 Wireless Intelligent Networks Center (WINC), School of Engineering and Applied Sciences, Nile University, Giza, Egypt Correspondence should be addressed to Ali Wagdy Mohamed; aliwagdy@gmail.com Received 15 October 2020; Revised 26 October 2020; Accepted 30 October 2020; Published 8 December 2020 Academic Editor: Ahmed Mostafa Khalil Copyright © 2020 Said Ali Hassan et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is work is dedicated to the economic scheduling of the required electric stations in the upcoming 10-year long-term plan. e calculation of the required electric stations is carried out by estimating the yearly consumption of electricity over a long-time plan and then determining the required number of stations. e aim is to minimize the total establishing and operating costs of the stations based on a mathematical programming model with nonlinear objective function and integer decision variables. e introduced model is applied for a real practical case study to conclude the number of yearly constructed stations over a long-term plan in the electricity sector in Jeddah City, Saudi Arabia. e current planning method is based only on intuition by constructing the same number of required stations in each year without searching for better solutions. To solve the introduced mathematical model, a novel recent gaining sharing knowledge-based algorithm, named GSK, has been used. e Augmented Lagrangian Method (ALM) is applied to transform the constrained formulation to become unconstrained with penalization to the objective function. According to the obtained results of the real case study, the proposed GSK with ALM approved an ability to solve this case with respect to convergence, efficiency, quality, and robustness. 1.Introduction In the coming years, the population projection is expected to rise worldwide, and this should be accomplished through an enough increase in the supply of electricity to cover the anticipated higher demand. Expert opinions suggest that the expected load demand is a key factor needed for preparing the potential power needs. Planning authorities around the world state that the forecast of the population is to be continuously increasing [1]. is increase should be balanced by an enough increase in the supply of electricity. Since electricity demand is in a direct relation to the anticipated population growth, the electricity company should support the current network by installing addi- tional stations to meet the growing demand [2]. e in- frastructure utilities demand such as water, electricity, wastewater, and communication would surpass propor- tion to the population growth and the expansion of new urban areas. e responsible authorities are required to support the corresponding networks by installing new stations to meet the growing demand and prevent busi- ness disruption and economic losses due to electricity failures [3]. Hindawi Complexity Volume 2020, Article ID 6675741, 13 pages https://doi.org/10.1155/2020/6675741