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

“…The test suite of benchmark function is recently designed for the special session of EAs competition in IEEE Congress on Evolutionary Computation (IEEE-CEC′13). The suggested algorithm has approximated promising solutions with good convergence and diversity maintenance for most of the used bound constrained single optimization problems. …”

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

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

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Optimizing transparent photovoltaic integration with battery energy storage systems in greenhouse: a daily light integral-constrained economic analysis considering BESS degradation by Gholami, Mohammadreza

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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities by Zouein, P. P.

“…loosely versus tightly constrained layouts. In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.…”
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Optimizing transparent photovoltaic integration with battery energy storage systems in greenhouse: a daily light integral-constrained economic analysis considering BESS degradation by Mohammadreza Gholami (17032317)

Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

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Whale optimization algorithm: analysis and full survey by Abualigah, Laith

“…Various adaptations and hybridizations of the WOA are reviewed, including adaptive strategies, constrained and multiobjective optimization extensions, and combinations with other algorithms. …”
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Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

“…In this paper, we design and adapt a Squirrel Search Algorithm (SSA) for the unconstrained and constrained portfolio optimization problems. …”
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Island flower pollination algorithm for global optimization by Al-Betar, Mohammed Azmi

“…Comparing the results of IsFPA with those of state-of-the-art methods which are FPA, genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), multi-verse optimizer (MVO), island bat algorithm (iBA), and island harmony search (iHS), the comparison results show that the IsFPA is able to control the diversity and improves the outcomes where IsFPA is ranked first followed by FPA, iBA, iHS, GSA, MVO, GA, PSO, respectively, based on the Friedman test with Holm and Hochberg as post hoc statistical test.…”
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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization by Alhadhrami, Esra Ebrahim

“…The Q value plays a crucial role in estimating future state values within a Kalman filter tracking system. Proximal Policy Optimization (PPO), a state-of-the-art policy optimization algorithm, was employed to determine the optimal Q value that enhances tracking performance, as measured by Root Mean Square Error (RMSE). …”
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT) by AlHamaydeh, Mohammad

“…The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…In particular, the Proximity Policy Optimization (PPO) reinforcement algorithm is used to discover a policy for sensor selection that results in optimum sensor resource allocation. …”
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Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm by Abido, M. A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by 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.…”

A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement by 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 VAR Dispatch Using Strength Pareto Evolutionary Algorithm by Abido, M.A.

“…In this paper, strength Pareto evolutionary algorithm (SPEA) for optimal reactive power (VAR) dispatch problem is presented. …”
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Multiobjective optimal power flow using strength Pareto evolutionary algorithm by Abido, M.A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. …”
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A novel multiobjective evolutionary algorithm for optimal reactive power dispatch problem by Abido, M.A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. …”
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Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. Jointly optimized RVQ (JORVQ) is an effective design algorithm for minimizing the overall quantization error. …”
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