Search alternatives:
spatial optimization » spatial organization (Expand Search), path optimization (Expand Search), swarm optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
genes based » gene based (Expand Search), lens based (Expand Search)
based codon » based color (Expand Search), based cohort (Expand Search), based action (Expand Search)
spatial optimization » spatial organization (Expand Search), path optimization (Expand Search), swarm optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
genes based » gene based (Expand Search), lens based (Expand Search)
based codon » based color (Expand Search), based cohort (Expand Search), based action (Expand Search)
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1
DE algorithm flow.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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2
Test results of different algorithms.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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3
Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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4
Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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5
Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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6
Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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7
Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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8
Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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9
Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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10
Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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11
Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG
Published 2023“…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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12
Plan frame of the house.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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13
Ablation test results.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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14
Hyperparameter selection test.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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15
Multiple index test results of different methods.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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16
Backtracking strategy diagram.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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17
Comparison of differences in literature methods.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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18
New building interior space layout model flow.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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19
Schematic of iteration process of IDE-IIGA.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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20
Schematic diagram of IGA chromosome coding.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”