Non-uniform mapping in real-coded genetic algorithms

Dhebar, Yashesh; Deb, Kalyanmoy; Bandaru, Sunith

doi:10.1109/cec.2014.6900621

“…We also provide a comparison of the top 3 NLopt algorithms (A11, A13 and A14) on the CEC 2014 benchmarks with other reference algorithms. These include the United Multi-Operator Evolutionary Algorithms (UMOEA) [13], Success-History based Adaptive Differential Evolution using linear population size reduction (L-SHADE) [58], Differential Evolution with Replacement Strategy (RSDE) [69], Memetic Differential Evolution Based on Fitness Euclidean-Distance Ratio (FERDE) [49], Partial Opposition-Based Adaptive Differential Evolution (POBL-ADE) [23], Mean-Variance Mapping Optimization (MVMO) [14], rmalschcma [39], Opt Bees [38], Fireworks Algorithm with Differential Mutation (FWA-DE) [72], Non-uniform Real-coded Genetic Algorithm (NRGA) [71], b3e3pbest [5] and DE b6e6rl [43].…”

Section: Results On Cec 2014 Benchmarksmentioning

confidence: 99%

Benchmarking NLopt and state-of-art algorithms for Continuous Global Optimization via Hybrid IACO$_\mathbb{R}$

Kumar,

Soman

2015

Preprint

0

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This paper presents a comparative analysis of the performance of the Incremental Ant Colony algorithm for continuous optimization (IACO R ), with different algorithms provided in the NLopt library. The key objective is to understand how the various algorithms in the NLopt library perform in combination with the Multi Trajectory Local Search (Mtsls1) technique. A hybrid approach has been introduced in the local search strategy by the use of a parameter which allows for probabilistic selection between Mtsls1 and a NLopt algorithm. In case of stagnation, the algorithm switch is made based on the algorithm being used in the previous iteration. The paper presents an exhaustive comparison on the performance of these approaches on Soft Computing (SOCO) and Congress on Evolutionary Computation (CEC) 2014 benchmarks. For both benchmarks, we conclude that the best performing algorithm is a hybrid variant of Mtsls1 with BFGS for local search.

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“…These include the United Multi-Operator Evolutionary Algorithms (UMOEA) [13], Success-History based Adaptive Differential Evolution using linear population size reduction (L-SHADE) [58], Differential Evolution with Replacement Strategy (RSDE) [69], Memetic Differential Evolution Based on Fitness Euclidean-Distance Ratio (FERDE) [49], Partial Opposition-Based Adaptive Differential Evolution (POBL-ADE) [23], Mean-Variance Mapping Optimization (MVMO) [14], rmalschcma [39], Opt Bees [38], Fireworks Algorithm with Differential Mutation (FWA-DE) [72], Non-uniform Real-coded Genetic Algorithm (NRGA) [71], b3e3pbest [5] and DE b6e6rl [43].…”

Section: Results On Cec 2014 Benchmarksmentioning

confidence: 99%

Benchmarking NLopt and state-of-the-art algorithms for continuous global optimization via IACOR

Kumar

¹

,

Soman

²

,

Jayadeva

³

2016

Swarm and Evolutionary Computation

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This paper presents a comparative analysis of the performance of the Incremental Ant Colony algorithm for continuous optimization (IACO R ), with different algorithms provided in the NLopt library. The key objective is to understand how the various algorithms in the NLopt library perform in combination with the Multi Trajectory Local Search (Mtsls1) technique. A hybrid approach has been introduced in the local search strategy by the use of a parameter which allows for probabilistic selection between Mtsls1 and a NLopt algorithm. In case of stagnation, the algorithm switch is made based on the algorithm being used in the previous iteration. The paper presents an exhaustive comparison on the performance of these approaches on Soft Computing (SOCO) and Congress on Evolutionary Computation (CEC) 2014 benchmarks. For both benchmarks, we conclude that the best performing algorithm is a hybrid variant of Mtsls1 with BFGS for local search.

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“…Direct experiments 3 have shown the limits of GSP regarding the imaging perspective. We estimate the acceptable grid dimensions under ASML scanner boundaries and restrictions using imaging simulations.…”

Section: Imaging Simulationmentioning

confidence: 99%

Grid-supported EUV pellicles: A theoretical investigation for added value

Dhalluin

¹

,

Winter

²

,

Scaccabarozzi

³

et al. 2015

Photomask Japan 2015: Photomask and Next-Generation Lithography Mask Technology XXII

4

0

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EUV pellicle membranes are being pursued to protect scanner images from repeating defects caused by reticle fall-on particle defects. Because most materials highly absorb EUV, pellicle membranes must be ultrathin. In an attempt to increase the strength of the ultrathin membranes, grid-supported pellicle membranes have been proposed. In this study we compare grid-supported pellicles (GSP) over free-standing pellicles (FSP). We considered imaging, thermal, mechanical, and thermo-mechanical characteristics. Finite Element Methods (FEM) was used to investigate the thermal, and (thermo-)mechanical behavior of pellicles. The maximum temperature reached under operational conditions by the pellicle film was determined. Using a thermo-mechanical analysis wrinkling behavior was quantified. The mechanical analysis considered the influence of grid structures on the sagging behavior, on crack propagation, on the pellicle film resistance to collision with solid particles, and on the resistance to shocks on the pellicle frame. The analysis shows that GSP that meets imaging requirements will not bring any advantages over FSP.

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Non-uniform mapping in real-coded genetic algorithms

Cited by 22 publications

References 2 publications

Benchmarking NLopt and state-of-art algorithms for Continuous Global Optimization via Hybrid IACO$_\mathbb{R}$

Benchmarking NLopt and state-of-art algorithms for Continuous Global Optimization via Hybrid IACO$_\mathbb{R}$

Benchmarking NLopt and state-of-the-art algorithms for continuous global optimization via IACOR

Grid-supported EUV pellicles: A theoretical investigation for added value

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