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Comparison of case and control groups in terms of postoperative complications, outcomes, and survival in total hip arthroplasty patients with and without COVID-19

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dc.contributor.author Cinar, Fadime
dc.date.accessioned 2024-03-19T07:18:00Z
dc.date.available 2024-03-19T07:18:00Z
dc.date.issued 2023
dc.identifier.issn 2296-858X
dc.identifier.uri http://hdl.handle.net/11547/11338
dc.description.abstract In this study, a new way to improve the Heuristic Bubble Algorithm (HBA) is presented. HBA is a nature-inspired algorithm, which is a new approach to and initially implemented for, vehicle routing problems of pickup and delivery (VRPPD). Later, it was reinforced to solve other routing problems, such as vehicle routing problem with time windows (VRPTW), and vehicle routing problem with stochastic demands (VRPSD). HBA is a greedy algorithm. It will mostly find local optimal solutions. The proposed method is an improvement over HBA enabling it to reach the global minimum. It uses specialized simulated annealing methods in its operators. A well-known data-set is used to benchmark the proposed method. Better results over HBA and some best results in literature are recorded. tr_TR
dc.language.iso en tr_TR
dc.relation.ispartofseries 10;
dc.subject CYTOKINES tr_TR
dc.subject DELIRIUM tr_TR
dc.title Comparison of case and control groups in terms of postoperative complications, outcomes, and survival in total hip arthroplasty patients with and without COVID-19 tr_TR
dc.type Article tr_TR


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