Feedback-Based Adaptive Crossover-Rate in Evolutionary Computation
Authors: Xiaoyuan Guan, Tianyi Yang, Chunliang Zhao, Yuren Zhou
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments and analysis show our approach effectively optimizes bi-objective problems COCZ and LOTZ in Θ(n) time during crossover, outperforming conventional crossover multi-objective evolutionary algorithms (C-MOEA) which require O(n log n) steps. For the tri-objective problem Hierarchical COCZ, our approach guarantees an expected runtime of Θ(n2 log n), while C-MOEA needs at least Ω(n2 log n) and at most O(n2 log2 n) steps. We conduct the corresponding experiments for the three problems studied to verify the theoretical analysis. The empirical results are shown in Figure 3. |
| Researcher Affiliation | Academia | School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China Key Laboratory of Machine Intelligence and Advanced Computing, MOE, Guangzhou, China School of Data and Science, Qingdao Universityof Science and Technology,Oingdao, China School of Software Engineering, Sun Yat-sen University, Zhuhai, China |
| Pseudocode | Yes | Algorithm 1 Initialization (Phase 1) and Algorithm 2 C-MOEA-MCD are provided. |
| Open Source Code | No | The paper does not provide any explicit statements about open-source code availability or links to a code repository. |
| Open Datasets | No | The paper analyzes performance on defined problems (COCZ, LOTZ, Hierarchical-COCZ) which are functions/structures, not traditional publicly available datasets with access information. |
| Dataset Splits | No | The paper discusses theoretical problems and runtime analysis, not dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | Yes | For all the problems, denote by n the problem size, we let α = log(n 1), pr = 0.5, and we initialize the preference score list for each (dimension reduced) bi-objective string as 1n 1. |