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<bibitem type="M">   <ARLID>0507126</ARLID> <utime>20240103222344.0</utime><mtime>20190731235959.9</mtime>    <DOI>10.1137/1.9781611974683.ch11</DOI>           <title language="eng" primary="1">Truss topology design by conic linear optimization</title>  <specification> <book_pages>648</book_pages> <page_count>13 s.</page_count> <media_type>P</media_type> </specification>   <serial><ARLID>cav_un_epca*0507125</ARLID><ISBN>978-1-61197-467-6</ISBN><title>Advances and Trends in Optimization with Engineering Applications</title><part_num/><part_title/><page_num>135-147</page_num><publisher><place>Philadelphia</place><name>SIAM, Society for Industrial and Applied Mathematics</name><year>2017</year></publisher><editor><name1>Terlaky</name1><name2>Tamas</name2></editor><editor><name1>Anjos</name1><name2>Miguel</name2></editor><editor><name1>Shabbir</name1><name2>Ahmed</name2></editor></serial>    <keyword>truss topology optimization</keyword>   <keyword>conic optimization</keyword>    <author primary="1"> <ARLID>cav_un_auth*0101131</ARLID> <full_dept language="cz">Matematická teorie rozhodování</full_dept> <full_dept language="eng">Department of Decision Making Theory</full_dept> <department language="cz">MTR</department> <department language="eng">MTR</department> <full_dept>Department of Decision Making Theory</full_dept> <share>100</share> <name1>Kočvara</name1> <name2>Michal</name2> <institution>UTIA-B</institution> <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>   <source> <url>http://library.utia.cas.cz/separaty/2019/MTR/kocvara-0507126.pdf</url> </source>        <cas_special>  <abstract language="eng" primary="1">This chapter can be viewed as a complement to Chapter 2 (Truss Topology Design by Linear Optimization). We will use the same mechanical model of trusses and, whenever possible, the same notation. In Chapter 2, the truss topology design problem is formulated and solved as a linear optimization (LO) problem. In this chapter, we will introduce alternative formulations using conic linear optimization (CLO). In particular, we will present linear second-order cone optimization (SOCO) and linear semidefinite optimization (SDO) formulations of the minimum volume and minimum compliance problems. All formulations will be developed in the “primal” variables (bar cross-sectional areas) and the “dual” variables (displacements). </abstract>     <RIV>BA</RIV> <FORD0>10000</FORD0> <FORD1>10100</FORD1> <FORD2>10101</FORD2>    <reportyear>2020</reportyear>      <num_of_auth>1</num_of_auth>  <inst_support> RVO:67985556 </inst_support>  <permalink>http://hdl.handle.net/11104/0298530</permalink>   <confidential>S</confidential>        <arlyear>2017</arlyear>       <unknown tag="mrcbU14"> SCOPUS </unknown> <unknown tag="mrcbU24"> PUBMED </unknown> <unknown tag="mrcbU34"> WOS </unknown> <unknown tag="mrcbU63"> cav_un_epca*0507125 Advances and Trends in Optimization with Engineering Applications SIAM, Society for Industrial and Applied Mathematics 2017 Philadelphia 135 147 978-1-61197-467-6 </unknown> <unknown tag="mrcbU67"> 340 Terlaky Tamas </unknown> <unknown tag="mrcbU67"> 340 Anjos Miguel </unknown> <unknown tag="mrcbU67"> 340 Shabbir Ahmed </unknown> </cas_special> </bibitem>