A Weighting-Based Tabu Search Algorithm for the p-Next Center Problem
Authors: Qingyun Zhang, Zhouxing Su, Zhipeng Lü, Lingxiao Yang
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experimental studies on 413 benchmark instances demonstrate that WTS outperforms the state-of-the-art methods in the literature. Specifically, WTS improves 12 previous best known results and matches the optimal results for all remaining 401 ones in a much shorter time than other algorithms. More importantly, WTS reaches the lower bounds for 10 instances for the first time. |
| Researcher Affiliation | Academia | Huazhong University of Science and Technology, China {qingyun zhang, suzhouxing, zhipeng.lv, yanglingxiao}@hust.edu.cn |
| Pseudocode | Yes | Algorithm 1 The main framework of the WTS algorithm; Algorithm 2 Closing a center; Algorithm 3 Opening a center; Algorithm 4 Find the best swap pair |
| Open Source Code | No | The paper does not provide any explicit statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | There are 413 instances for the p NCP generated from 40 p-median instances from OR-Library [Londe et al., 2021]. The number of vertices n ranges from 10 to 900, and the number of centers p distributes between 5 and 450. [Beasley, 1990] John E Beasley. OR-library: distributing test problems by electronic mail. J. Oper. Res. Soc., 41(11):1069 1072, 1990. |
| Dataset Splits | No | The paper evaluates its algorithm on 413 benchmark instances but does not specify a training, validation, or test split in the traditional machine learning sense for these instances. The instances serve as the problem sets to be solved. |
| Hardware Specification | Yes | All our experiments are run on Windows x64 with an Intel Core i7-10700 2.90 GHz CPU. |
| Software Dependencies | Yes | The MIP models proposed by [Albareda Sambola et al., 2015] were solved with IBM ILOG CPLEX 12.10 solver |
| Experiment Setup | Yes | We performed 20 independent runs on each instance under a 60-second time limit. The computational platform for the reference algorithm GRASPVNS is Intel Core 2 Duo E8400 (3 GHz) with 4 GB RAM. The reference algorithms ILS and BRKGA are tested on an Intel Xeon E5530 CPU at 2.40 GHz and 120 GB of RAM running Cent OS Linux and the time limit for each instance is 1800 seconds. |