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10.1073/pnas.1421853112 http://scihub22266oqcxt.onion/10.1073/pnas.1421853112 C4311855!4311855!25561535     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=25561535&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2015 ; 112 (3): 663-8 Nephropedia Template TP {{tp|p=25561535|t=2015. Finding long chains in kidney exchange using the traveling salesman problem |pdf=|usr=}}{{25561535}} gab.com Text Finding long chains in kidney exchange using the traveling salesman problem JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=25561535 #FOAvip There are currently more than 100,000 patients on the waiting list in the United States for a kidney transplant from a deceased donor. To address this shortage, kidney exchange programs allow patients with living incompatible donors to exchange donors through cycles and chains initiated by altruistic nondirected donors. To determine which exchanges will take place, kidney exchange programs use algorithms for maximizing the number of transplants under constraints about the size of feasible exchanges. This problem is NP-hard, and algorithms previously used were unable to optimize when chains could be long. We developed two algorithms that use integer programming to solve this problem, one of which is inspired by the traveling salesman, that together can find optimal solutions in practice. Twit Text FOAVip Finding long chains in kidney exchange using the traveling salesman problem ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=25561535 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25561535 #FOAvip English Wikipedia <ref>{{Cite pmid|25561535}}</ref> Finding long chains in kidney exchange using the traveling salesman problem #MMPMID25561535 Anderson R; Ashlagi I; Gamarnik D; Roth AE Proc Natl Acad Sci U S A 2015[Jan]; 112 (3): 663-8 PMID25561535show ga There are currently more than 100,000 patients on the waiting list in the United States for a kidney transplant from a deceased donor. To address this shortage, kidney exchange programs allow patients with living incompatible donors to exchange donors through cycles and chains initiated by altruistic nondirected donors. To determine which exchanges will take place, kidney exchange programs use algorithms for maximizing the number of transplants under constraints about the size of feasible exchanges. This problem is NP-hard, and algorithms previously used were unable to optimize when chains could be long. We developed two algorithms that use integer programming to solve this problem, one of which is inspired by the traveling salesman, that together can find optimal solutions in practice. äFinding long chains in kidney exchange using the traveling salesman pr(epmc).pdf DeepDyve Pubget Overpricing