Greedy optimization algorithm. by Alexis Bénichou (19832361)

Code and data. by Shangyang Jin (21772466)

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The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

Optimization-Driven Steganographic System Based on Fused Maps and Blowfish Encryption by Ahmed Aljughaiman (21793526)

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Parameters of each algorithm. by Nanqi Li (11640083)

data_code.zip by Mengmeng Gong (20129994)

“…In this study, we conduct an in-depth investigation of a novel adaptive covariance inflation algorithm (t-X) within the framework of an observation system simulation experiment (OSSE) based on anintermediate coupled model (ICM) and the Ensemble Adjustment KF(EAKF), aiming to develop a joint approach for optimizing both model parameters and initial fields simultaneously. …”

Path length variation diagram of each algorithm. by Yun Qi (560401)

“…These enhancements are compared against single-strategy improved WOAs.Subsequently, path planning simulations were conducted using several extracted algorithms and grid-based methods. The results demonstrate that the optimal path length achieved by the Multi-Strategy WOA (MSWOA) is 41.7% shorter than that of the standard WOA, 42.3% shorter than WOA-1, and 48.5% shorter than PSO for the shortest path. …”

Simulation results of each algorithm path map. by Yun Qi (560401)

“…These enhancements are compared against single-strategy improved WOAs.Subsequently, path planning simulations were conducted using several extracted algorithms and grid-based methods. The results demonstrate that the optimal path length achieved by the Multi-Strategy WOA (MSWOA) is 41.7% shorter than that of the standard WOA, 42.3% shorter than WOA-1, and 48.5% shorter than PSO for the shortest path. …”

The effect of each parameter on the peak value. by Shangyang Jin (21772466)

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RRT algorithm. by Naeem Ul Islam (19837966)

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RRT* algorithm. by Naeem Ul Islam (19837966)

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Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. by Jiren CAO (20442214)

RE-RRT* algorithm. by Naeem Ul Islam (19837966)

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Reward outcomes for each combination of task cue and policy in the experiment. by Sam Hall-McMaster (10343795)

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Data and code resources. by Sam Hall-McMaster (10343795)

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Data and code used in this article. by Yazhen Zhu (3595430)

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Schematic result of RRT algorithm. by Naeem Ul Islam (19837966)

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The RRT algorithm’s software architecture. by Naeem Ul Islam (19837966)

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Task sequences for each AGV when using Hungarian algorithm in the front end of IPSO(+B). by Yazhen Zhu (3595430)

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Task sequences for each AGV when using greedy algorithm in the front end of IPSO(+B). by Yazhen Zhu (3595430)

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