Search alternatives:
basis optimization » based optimization (Expand Search), task optimization (Expand Search), acid optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
basis optimization » based optimization (Expand Search), task optimization (Expand Search), acid optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (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
DMTD algorithm.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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4
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5
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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6
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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7
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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8
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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9
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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10
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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11
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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12
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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13
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. …”
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14
EITO<sub>P</sub> with flexible trip time.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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15
Energy consumption in the PPO process.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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16
Speed limits.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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17
Running time in the PPO process.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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18
Speed limits and gradients from RJ to WYJ.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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19
EITO<sub>E</sub> speed distance profile.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”
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20
Speed limits and gradient from SJZ to XHM.
Published 2025“…On the basis of EITO<sub>E</sub>, we propose EITO<sub>P</sub> algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”