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An Extreme Point Algorithm For A Local Minimum Solution To The Quadratic Assignment Problem
Published 2020“…Then an extreme point algorithm for QAP is proposed.…”
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Digital circuit design through simulated evolution (SimE)
Published 2003“…In this paper, the use of simulated evolution (SimE) algorithm in the design of digital logic circuits is proposed. …”
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Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement
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Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms
Published 2012“…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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Simulated evolution for timing and low power VLSI standard cell placement
Published 2020“…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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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”
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Fuzzy simulated evolution for power and performance optimization ofVLSI placement
Published 2001“…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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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…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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Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement
Published 2004“…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
Published 2020“…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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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
Published 2023“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review
Published 2022“…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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Incremental Genetic Algorithm
Published 2006“…Classical Genetic Algorithms (CGA) are known to find good sub-optimal solutions for complex and intractable optimization problems. …”
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Topics in graph algorithms
Published 2003“…Coping with computational intractability has inspired the development of a variety of algorithmic techniques. The main challenge has usually been the design of polynomial time algorithms for NP-complete problems in a way that guarantees some, often worst-case, satisfactory performance when compared to exact (optimal) solutions. …”
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FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT
Published 2006“…SE is hybridized with force directed algorithm to speed-up the search. The proposed schemes are compared with previously presented SE based heuristics. …”
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Centroid-Based Differential Evolution with Composite Trial Vector Generation Strategies for Neural Network Training
Published 2023“…Differential evolution (DE), a popular population-based metaheuristic algorithm, is an interesting alternative for tackling challenging optimisation problems. …”
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