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

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

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

“…This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. …”
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Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm by 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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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 power flow using strength Pareto evolutionary algorithm by 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 novel multiobjective evolutionary algorithm for optimal reactive power dispatch problem by 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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Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests by 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.…”

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

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Tabu search based circuit optimization by Sait, Sadiq M.

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

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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.…”

CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction by Khot, Mohammed Taha Shafiq

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An evolutionary algorithm for network topology design by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem, dictated by physical and technological constraints and must optimize several objectives. …”
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A multi-objective planning approach for optimal DG allocation for droop based microgrids by Shaaban, Mostafa

“…This paper proposes a multi-objective planning approach to determine the optimal DG locations for droop-based microgrids. A secondary control operating region is mathematically formulated and incor-porated in the multi-objective optimization problem to constrain the optimal droop characteristic within the acceptable frequency and voltage thresholds. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …”
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Environmental/economic power dispatch using multiobjective evolutionary algorithms by Abido, M.A.

“…The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

“…To intensify the search, we have also incorporated Tabu Search-based characteristics in the allocation phase of the SE algorithm. …”
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A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

“…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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The survey of cluster based data collection process for iot enabled wireless sensor network using several optimization technique by Abirami, R.

“…The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray Wolf Optimization and Water-Cycle Algorithms, and specialised protocols of clustering, routing and data aggregation. …”
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