{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:13:15Z","timestamp":1760609595513,"version":"build-2065373602"},"reference-count":14,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T00:00:00Z","timestamp":1740528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Research in Jiangsu Province (Soft Science Research)","award":["BK20243046","SZS2022416"],"award-info":[{"award-number":["BK20243046","SZS2022416"]}]},{"name":"Science and Technology Innovation Support Platform Project","award":["BK20243046","SZS2022416"],"award-info":[{"award-number":["BK20243046","SZS2022416"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper introduces an improved Grover Adaptive Search (GAS) algorithm. The GAS algorithm has been prove to achieve quadratic acceleration in the Constrained Polynomial Binary Optimization (CPBO) problem. Nevertheless, the acceleration effect of the GAS algorithm can be decreased by the poor threshold selection. This article uses the Quantum Approximate Optimization Algorithm (QAOA) to improve the initial threshold selection, thereby accelerating the convergence speed of the original GAS algorithm. The acceleration effect of the improved GAS algorithm is presented by the Max-Cut problem and the CPBO problem.<\/jats:p>","DOI":"10.3390\/e27030240","type":"journal-article","created":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T04:46:37Z","timestamp":1740545197000},"page":"240","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An Improved GAS Algorithm"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9531-3369","authenticated-orcid":false,"given":"Zhijian","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Technology, Institute of Advanced Technology, University of Science and Technology of China, No. 96 Jinzhai Road, Hefei 230088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuchen","family":"He","sequence":"additional","affiliation":[{"name":"Yangtze Delta Region Industrial Innovation Center of Quantum and Information Technology, Suzhou 215100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3962-5772","authenticated-orcid":false,"given":"Tian","family":"Luan","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, Institute of Advanced Technology, University of Science and Technology of China, No. 96 Jinzhai Road, Hefei 230088, China"},{"name":"Yangtze Delta Region Industrial Innovation Center of Quantum and Information Technology, Suzhou 215100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Long","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, Institute of Advanced Technology, University of Science and Technology of China, No. 96 Jinzhai Road, Hefei 230088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1287\/ijoc.2017.0798","article-title":"What works best when? A systematic evaluation of heuristics for Max-Cut and QUBO","volume":"30","author":"Dunning","year":"2018","journal-title":"INFORMS J. Comput."},{"key":"ref_2","unstructured":"Dury, B., and Di Matteo, O. (2020). A QUBO formulation for qubit allocation. arXiv."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Arora, S. (1998, January 24\u201326). The approximability of NP-hard problems. Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, Dallas, TX, USA.","DOI":"10.1145\/276698.276784"},{"key":"ref_4","unstructured":"Woeginger, G.J. (2001, January 5\u20139). Exact algorithms for NP-hard problems: A survey. Proceedings of the Combinatorial Optimization\u2014Eureka, You Shrink! Jack Edmonds 5th International Workshop, Aussois, France. Revised Papers."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"B\u00e4rtschi, A., and Eidenbenz, S. (2020, January 12\u201316). Grover mixers for QAOA: Shifting complexity from mixer design to state preparation. Proceedings of the 2020 IEEE International Conference on Quantum Computing and Engineering (QCE), Denver, CO, USA.","DOI":"10.1109\/QCE49297.2020.00020"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Choi, J., and Kim, J. (2019, January 16\u201318). A tutorial on quantum approximate optimization algorithm (QAOA): Fundamentals and applications. Proceedings of the 2019 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Republic of Korea.","DOI":"10.1109\/ICTC46691.2019.8939749"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Guerreschi, G.G., and Matsuura, A.Y. (2019). QAOA for Max-Cut requires hundreds of qubits for quantum speed-up. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-43176-9"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s11128-022-03766-5","article-title":"Benchmarking the performance of portfolio optimization with QAOA","volume":"22","author":"Brandhofer","year":"2022","journal-title":"Quantum Inf. Process."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"428","DOI":"10.22331\/q-2021-04-08-428","article-title":"Grover adaptive search for constrained polynomial binary optimization","volume":"5","author":"Gilliam","year":"2021","journal-title":"Quantum"},{"key":"ref_10","unstructured":"Federer, M., Lenk, S., M\u00fcssig, D., Wappler, M., and L\u00e4ssig, J. (2023, January 26\u201328). Constrained Grover Adaptive Search for Optimization of the Bidirectional EV Charging Problem. 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Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, Phoenix, AZ, USA.","DOI":"10.1145\/3313276.3316364"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/27\/3\/240\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:42:52Z","timestamp":1760028172000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/27\/3\/240"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,26]]},"references-count":14,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["e27030240"],"URL":"https:\/\/doi.org\/10.3390\/e27030240","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2025,2,26]]}}}