Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement by Sait, Sadiq M.

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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…Abstract This paper presents a Fuzzy Simulated Evolution algorithm for VLSI standard cell placement with the objective of minimizing power, delay and area. …”
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Fuzzy simulated evolution for power and performance optimization ofVLSI placement by Sait, Sadiq M.

“…This is a hard multiobjective combinatorial optimization problem with no known exact and efficient algorithm that can guarantee finding a solution of specific or desirable quality. …”
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Cooperative Co-evolution using LSHADE with Restarts For The CEC15 Benchmarks by El-Abd, Mohammed

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Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement by Sait, Sadiq M.

“…In this work, a fast hybrid algorithm is designed to address this problem. The algorithm employs simulated evolution (SE), an iterative search heuristic that comprises three steps: evaluation, selection and allocation. …”
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A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments by Barada, Hassan

“…The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. …”
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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review by Chakraborty, Sanjoy

“…Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. …”
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FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT by Sait, Sadiq M.

“…A major difculty with such multi-objective combinatorial optimization problems is the existence of a very large solution search space, one of which is the desired optimal solution. …”
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Centroid-Based Differential Evolution with Composite Trial Vector Generation Strategies for Neural Network Training by El-Abd, Mohammed

“…Differential evolution (DE), a popular population-based metaheuristic algorithm, is an interesting alternative for tackling challenging optimisation problems. …”
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A new method for broad‐scale modeling and projection of plant assemblages under climatic, biotic, and environmental cofiltering by Alessandro Ferrarini (3951098)

An Extreme Point Algorithm For A Local Minimum Solution To The Quadratic Assignment Problem by Fedjki, C.A.

“…In this paper the network structure of basic solutions to the quadratic assignment problem (QAP) is revisited. …”
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An Extreme Point Algorithm For A Local Minimum Solution To The Quadratic Assignment Problem by Fedjki, C.A.

“…Then an extreme point algorithm for QAP is proposed.…”
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Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash by Ilias K. Nikolaidis (9217172)

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”

Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm by Hina Gupta (21842246)

On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar (18560506)

Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW) by Ayesha Maroof (17984053)

“…This research introduces a cutting-edge Hybrid Genetic Algorithm-Solomon Insertion Heuristic (HGA-SIH) solution, reinforced by the powerful Solomon Insertion constructive heuristic to solve the VRPTW as an NP-hard problem. …”

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. …”

Salp swarm algorithm: survey, analysis, and new applications by Abualigah, Laith

“…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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