A new metaheuristic optimization method: the algorithm of the innovative gunner (AIG)

Pijarski, Paweł; Kacejko, P.

doi:10.1080/0305215x.2019.1565282

Cited by 51 publications

(22 citation statements)

References 30 publications

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“…The optimization method used in the research is called the Algorithm of the Innovative Gunner (AIG) [59]. It differs from other methods of generating new values of decision variables.…”

Section: Description Of the Optimisation Algorithmmentioning

confidence: 99%

“…Its innovativeness results from a specific and original way of determining subsequent solutions in the iterative process, which distinguishes it from other heuristic methods. The presentation of the AIG algorithm and its properties was made by the authors in [59], and its effectiveness was widely studied in [53]. Given that in the AIG algorithm we are dealing with a population of new solutions, it is characterized by a large exploration of the search space.…”

Section: Of 21mentioning

confidence: 99%

“…α and β are the "correction angles", drawn from the (−αmax, αmax) and (−βmax, βmax) range using a normal (or uniform) probability distribution.The block diagram of the AIG algorithm is shown inFigure 2[59].…”

mentioning

confidence: 99%

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Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations

Pijarski¹,

Kacejko²

2021

Energies

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Connecting a large number of distributed sources to the medium and low voltage grid poses many problems. The most important of these are the voltage changes inside the network, what can be observed when the power flow from these sources towards the HV/MV (High Voltage/Medium Voltage) transformer station. In particular, if the power consumption in nodes of the MV network is small and the distance between the place of installation of the source and the substation is large, increases and changes in voltage may be dangerous for the insulation of the network and burdensome for the consumers connected to it. The solution most frequently used to control voltage increases is the appropriate setting of the controller that affects the on-load tap changer of the MV/HV or even MV/LV (Medium Voltage/Low Voltage) transformer. It is also possible to regulate the reactive power of the sources and, of course, to limit their generated active power (curtailment of generation). The development of energy storage technology has made it possible to introduce consumers into the network, whose power can be controlled in a wide range. The article proposes the concept of an innovative voltage control system in the MV network, whose output values are three groups of parameters: HV/MV transformer ratio, reactive power of sources and active power of consumers connected in generation nodes. In the technological sense, it has been assumed that the loads are installations of electrolyzers used to produce “green hydrogen”, according to the P2G (Power to Gas) formula. The tests consisting in the execution of several hundred calculation cycles for the IEEE 37 test network, using the Monte Carlo simulation, have shown that the subordination of the hydrogen production process to the objectives of voltage control in the MV network clearly contributes to stabilizing its value, while meeting the technological requirements. The control variables of the proposed control system are the result of the optimization algorithm described in the article, the function of which is the quality of network voltage.

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“…The optimization method used in the research is called the Algorithm of the Innovative Gunner (AIG) [59]. It differs from other methods of generating new values of decision variables.…”

Section: Description Of the Optimisation Algorithmmentioning

confidence: 99%

Section: Of 21mentioning

confidence: 99%

See 1 more Smart Citation

Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations

Pijarski¹,

Kacejko²

2021

Energies

Self Cite

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“…Nazari-Heris et al [26], Zhao et al [27], Sameer et al [28], Reddy et al [29], Stützle et al [30], Pijarski and Piotr [31], Yapici and Cetinkaya [32], Dede et al [33], Grzywiński et al [34], Kaveh et al [35], Kaveh et al [36] and Kaveh and Ilchi Ghazaan [37]. Following a description of the EVPS algorithm with a brief description of six other metaheuristic algorithms including VPS, GWO, HS, SSA, ECBO and GOA algorithms, is presented in the following subsections.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

Optimal Design of Steel Curved Roof Frames by Enhanced Vibrating Particles System Algorithm

Kaveh¹,

Vaez²,

Hosseini³

et al. 2019

Period. Polytech. Civil Eng.

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The paper presents an optimal design of steel curved roof frames with its roof being part of a circular arc. The elements of frames are tapered I-section members. In the objective function for optimization, two factors affecting the weight of frames are considered simultaneously. First, the roof slope angle as an effective variable on the values of the structural loading and second, the cross-section of members that are considered as continuous and discrete variables, respectively. In the range of 3 to 70 degrees, the optimum range of roof slope angles for steel curved roof frames, as well as precise value of the best roof slope angle, will be reported. Enhanced Vibrating Particles System (EVPS) algorithm is utilized for the optimal design of steel curved roof frames with tapered members. The performance and efficiency of the EVPS algorithm is compared with six other recently developed optimization algorithms including VPS, GWO, HS, SSA, ECBO and GOA algorithms. The effectiveness and performance of EVPS algorithm is proven. Frames design are performed using ANSI/AISC 360-05 speciﬁcations which strength, displacement and stability constraints are imposed on the frames.

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“…Focusing on a relatively simple concept and easy implementation, not requiring the gradient information, and bypassing most local optima indicate why metaheuristic optimization algorithms are more effective than other optimization methods and have become more prevalent in engineering applications in recent decades [8]. Algorithm of the Innovative Gunner (AIG) [9], Artificial Electric Field Algorithm (AEFA) [10], and Quantum Henry Gas Solubility (QHGS) [11] are examples of the recently developed metaheuristics. Metaheuristics as probabilistic solvers have been applied and developed for solving optimization problems in the field of civil engineering, such as structural optimization [12,13], damage detection [14,15], optimal design of retaining wall [16,17], etc.…”

Section: Introductionmentioning

confidence: 99%

Discrete Optimum Design of Planar Steel Curved Roof and Pitched Roof Portal Frames Using Metaheuristic Algorithms

Kaveh

Dastjerdi

Zaerreza

et al. 2021

Period. Polytech. Civil Eng.

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Portal frames are single-story frame buildings including columns and rafters, and their rafters can be either curved or pitched. These are used widely in the construction of industrial buildings, warehouses, gyms, fire stations, agricultural buildings, hangars, etc. The construction cost of these frames considerably depends on their weight. In the present research, the discrete optimum design of two types of portal frames including planar steel Curved Roof Frame (CRF) and Pitched Roof Frame (PRF) with tapered I-section members are presented. The optimal design aims to minimize the weight of these frame structures while satisfying some design constraints based on the requirements of ANSI/AISC 360-16 and ASCE 7-10. Four population-based metaheuristic optimization algorithms are applied to the optimal design of these frames. These algorithms consist of Teaching-Learning-Based Optimization (TLBO), Enhanced Colliding Bodies Optimization (ECBO), Shuffled Shepherd Optimization Algorithm (SSOA), and Water Strider Algorithm (WSA). Two main objectives are followed in this paper. The first one deals with comparing the optimized weight of the CRF and PRF structures with the same dimensions for height and span in two different span lengths (16.0 m and 32.0 m), and the second one is related to comparing the performance of the considered metaheuristics in the optimum design of these portal frames. The obtained results reveal that CRF is more economical than PRF in the fair comparison. Moreover, comparing the results acquired by SSOA with those of other considered metaheuristics reveals that SSOA has better performance for the optimal design of these portal frames.

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A new metaheuristic optimization method: the algorithm of the innovative gunner (AIG)

Cited by 51 publications

References 30 publications

Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations

Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations

Optimal Design of Steel Curved Roof Frames by Enhanced Vibrating Particles System Algorithm

Discrete Optimum Design of Planar Steel Curved Roof and Pitched Roof Portal Frames Using Metaheuristic Algorithms

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