{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T05:16:48Z","timestamp":1740028608614,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>Traveling Salesman Problem (TSP) is an NP-hard combinatorial optimization problem. Approximation algorithms have been used to reduce the worst-case factorial time complexity of TSP to non-deterministic polynomial time successfully. However, approximation methods result in a sub-optimal solution as they do not cover the search space adequately. Further, CPU implementations of approximation methods are too time consuming for large input instances. On the other hand, GPUs have been shown to be effective in exploiting data and memory level parallelism in large, complex problems.<\/jats:p>","DOI":"10.3233\/978-1-61499-882-2-221","type":"book-chapter","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:30:51Z","timestamp":1739979051000},"source":"Crossref","is-referenced-by-count":0,"title":["GPU-Based Iterative Hill Climbing Algorithm to Solve Symmetric Traveling Salesman Problem"],"prefix":"10.3233","author":[{"family":"Talawar Basavaraj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Yelmewad Pramod","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Advances in Parallel Computing","Big Data and HPC: Ecosystem and Convergence"],"original-title":[],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:34:18Z","timestamp":1739979258000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-881-5&spage=221&doi=10.3233\/978-1-61499-882-2-221"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-882-2-221","relation":{},"ISSN":["0927-5452"],"issn-type":[{"value":"0927-5452","type":"print"}],"subject":[],"published":{"date-parts":[[2018]]}}}