Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems حسب Agushaka, Jeffrey O.

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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems حسب Wali Khan Mashwani (14590504)

"…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …"

Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting حسب AlSayegh, Hadeel Yacoub

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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images حسب Abu Zitar, Raed

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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) حسب Bitar, Mandy

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Teaching–learning-based optimization algorithm: analysis study and its application حسب Abualigah, Laith

الموضوعات: "…Teaching–learning-based optimization algorithm…"
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A multi-objective planning approach for optimal DG allocation for droop based microgrids حسب Shaaban, Mostafa

"…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …"
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Tabu search based circuit optimization حسب Sait, Sadiq M.

"…In this paper we address the problem of optimizing mixed CMOS/BiCMOS circuits. The problem is formulated as a constrained combinatorial optimization problem and solved using an tabu search algorithm. …"
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter حسب Syed Rahman (569240)

"…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …"

Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests حسب Kenneth V. Price (17877002)

"…Simulations demonstrate that “U-scores” are much more effective than dominance when tasked with identifying the better of two algorithms. We validate U-scores by having them determine the winners of the CEC 2022 competition on single objective, bound-constrained numerical optimization.…"

Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm حسب Abido, M. A.

"…A new Strength Pareto Evolutionary Algorithm based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. …"
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Application of Red Deer Algorithm in Optimizing Complex functions حسب Zitar, Raed

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Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller حسب Sk. A., Shezan

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A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement حسب Minhas, Mahmood R.

"…In this paper, we present a parallel tabu search (TS) algorithm for efficient optimization of a constrained multiobjective VLSI standard cell placement problem. …"
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Multiobjective optimal power flow using strength Pareto evolutionary algorithm حسب Abido, M.A.

"…A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. …"
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011) حسب Kozhaya, David Elias

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An evolutionary algorithm for solving the geometrically constrained site layout problem حسب Zouein, P.

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A novel multiobjective evolutionary algorithm for optimal reactive power dispatch problem حسب Abido, M.A.

"…A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …"
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…"

Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems حسب Abualigah, Laith

"…The proposed method is based on enhancing the search process of the Prairie Dog Optimization Algorithm (PDOA) by using the primary updating mechanism of the Dwarf Mongoose Optimization Algorithm (DMOA). …"
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