Giza Pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization

Harifi, Sasan; Mohammadzadeh, Javad; Khalilian, Madjid; Ebrahimnejad, Sadoullah

doi:10.1007/s12065-020-00451-3

Cited by 81 publications

(40 citation statements)

References 50 publications

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“…Giza Pyramids Construction (GPC) is inspired by the ancient past and features a good metaheuristic algorithm to handle many problems. The inspiration of antiquity is to observe and reflect on the legacy of the past in order to understand the optimal methods, technologies, and strategies of that era [23]. The proposed algorithm is controlled by the movement of workers and pushing stone blocks on the road.…”

Section: Giza Pyramids Construction (Gpc)mentioning

confidence: 99%

“…Several artificial intelligence methods particularly the metaheuristic method have been used in solving ED problems in the past 5 years such as the chaotic bat algorithm (CBA) method which is a variant of the basic bat algorithm by entering chaotic sequences to improve its performance [4][5][6][7], Artificial Bee Colony Algorithm (ABC) which mimics the intelligent honeybee foraging behavior [8][9][10], grey wolf optimizer (GWO) inspired by hunting rules wolves and the grey wolf social hierarchy [11][12][13][14], and cuckoo search algorithm inspired by the interesting breeding behavior of cuckoo [15][16][17][18]. This paper will explore the potential of six metaheuristic methods, namely, Seagull Optimization Algorithm (SOA) [18], marine predator algorithm (MPA) [19], Sine Tree-Seed Algorithm (STSA) [20], Chimp Optimization Algorithm (ChOA) [21], Equilibrium Optimizer (EO) [22], and Giza Pyramids Construction (GPC) [23] in solving ELD problems. The test is using 2 different case studies and is based on several constraints.…”

Section: Introductionmentioning

confidence: 99%

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Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Aribowo

2022

Gazi University Journal of Science

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Section: Giza Pyramids Construction (Gpc)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Aribowo

2022

Gazi University Journal of Science

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“…The proposed algorithm is applied to IEEE 30 -bus system incorporating with two wind generators and one solar PV generator to verify its validity in obtaining the optimal solution for OPF problem with renewable energy sources during theoretical and practical conditions. Four other optimization techniques: Giza pyramids construction (GPC) [45], chaos game optimization (CGO) [46], flower pollination algorithm (FPA) [47] and artificial bee colony (ABC) [29] are applied to the proposed system to compare their results with the results of JS. The results of JS are also compared with the results obtained by SHADE-SF in [43].…”

Section: B Contribution and Paper Organizationmentioning

confidence: 99%

Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources

et al. 2021

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Today's electrical power system became more complex interconnected network that is expanding every day. The transmission lines of the power system are more severely loaded than ever before. Hence, the power system is facing many problems such as power losses increasing, voltage instability, line overloads, etc. The optimization of real and reactive powers due to the installation of energy resources at appropriate buses can minimize the losses and improve the voltage profile especially, for congested networks. As a result, the optimal power flow problem (OPF) is considered more important tool for the processes of planning and operation of power systems. OPF is a very significant tool for power system operators to meet the electricity demand of the consumers efficiently, and for the reliable operation of the power system. However, the incorporation of renewable energy sources (RESs) into the electrical grid is a very challenging problem due to their intermittent nature. In this paper, the proposed power flow model contains three different types of energy sources: thermal power generators representing the conventional energy sources, wind power generators (WPGs), and solar photovoltaic generators (SPGs) representing RESs. Uncertain output powers from WPGs and SPGs are forecasted with the aid of Weibull and lognormal probability distribution functions (PDF), respectively. The under and overestimation output powers of RESs are taken into consideration while formulating the objective function through adding a penalty and reserve cost, respectively. Moreover, carbon tax is imposed to the main objective function to help in reducing carbon emissions. A jellyfish search optimizer (JS) is employed to reach optimization in the modified IEEE 30-bus test system to validate its feasibility. To examine the effectiveness of the proposed JS algorithm, its simulation results are compared with the results of four other nature-inspired global optimization algorithms. The developed OPF algorithm considers several practical cases such as generation uncertainty of renewable energy sources, timevarying load and the ramp rate limits of thermal generators. The simulation results show the effectiveness of the JS algorithm in solving the OPF problem in terms of minimization of total generation cost and solution convergence.

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“…Harifi et al [33] initially proposed the GPC algorithm, simulating the building process of the pyramids in Giza. The GPC optimization is a new population-based metaheuristic optimization algorithm that is inspired by the movement of workers and stone blocks during the pyramid building.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia

et al. 2021

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Hybrid microgrids are presented as a solution to many electrical energetic problems. These microgrids contain some renewable energy sources such as photovoltaic (PV), wind and biomass, or a hybrid of these sources, in addition to storage systems. Using these microgrids in electric power generation has many advantages such as clean energy, stability in supplying power, reduced grid congestion and a new investment field. Despite all these microgrids advantages, they are not widely used due to some economic aspects. These aspects are represented in the net present cost (NPC) and the levelized cost of energy (LCOE). To handle these economic aspects, the proper microgrids configuration according to the quantity, quality and availability of the sustainable source of energy in installing the microgrid as well as the optimal design of the microgrid components should be investigated. The objective of this paper is to design an economic microgrid system for the Yanbu region of Saudi Arabia. This design aims to select the best microgrid configuration while minimizing both NPC and LCOE considering some technical conditions, including loss of power supply probability and availability index. The optimization algorithm used is Giza Pyramids Construction (GPC). To prove the GPC algorithm’s effectiveness in solving the studied optimization problem, artificial electric field and grey wolf optimizer algorithms are used for comparison purposes. The obtained results demonstrate that the best configuration for the selected area is a PV/biomass hybrid microgrid with a minimum NPC and LCOE of $319,219 and $0.208/kWh, respectively.

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Giza Pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization

Cited by 81 publications

References 50 publications

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources

Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia

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