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<bibitem type="J">   <ARLID>0602460</ARLID> <utime>20250317083850.1</utime><mtime>20241207235959.9</mtime>   <WOS>001250095200001</WOS>  <DOI>10.51680/ev.37.1.10</DOI>           <title language="eng" primary="1">FINDING AN OPTIMAL DISTRIBUTION STRATEGY PATH IN AN UNPREDICTABLE ENVIRONMENT</title>  <specification> <page_count>12 s.</page_count> <media_type>E</media_type> </specification>   <serial><ARLID>cav_un_epca*0595822</ARLID><ISSN>0353-359X</ISSN><title>Ekonomski Vjesnik</title><part_num/><part_title/><volume_id>37</volume_id><volume>1 (2024)</volume><page_num>139-150</page_num></serial>    <keyword>Supply chain optimization</keyword>   <keyword>probabilistic modelling</keyword>   <keyword>economic resilience</keyword>   <keyword>cost-benefit analysis</keyword>    <author primary="1"> <ARLID>cav_un_auth*0268047</ARLID> <name1>Petřík</name1> <name2>T.</name2> <country>CZ</country> </author> <author primary="0"> <ARLID>cav_un_auth*0329423</ARLID> <name1>Plajner</name1> <name2>Martin</name2> <institution>UTIA-B</institution> <full_dept language="cz">Matematická teorie rozhodování</full_dept> <full_dept>Department of Decision Making Theory</full_dept> <department language="cz">MTR</department> <department>MTR</department> <full_dept>Department of Decision Making Theory</full_dept> <country>CZ</country> <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>   <source> <url>https://library.utia.cas.cz/separaty/2024/MTR/plajner-0602460.pdf</url> </source> <source> <url>https://hrcak.srce.hr/ojs/index.php/ekonomski-vjesnik/article/view/28402</url>  </source>        <cas_special>  <abstract language="eng" primary="1">This article introduces an innovative method designed to optimize distribution strategies with respect to future uncertainty. It goes beyond the limitations of traditional scenario-based planning that often leads to suboptimal strategies due to the unpredictability of future developments and the challenge of accurately assigning probabilities to these scenarios. Consequently, the method allows selection of the most economically viable future strategy</abstract>     <result_subspec>JINE</result_subspec> <RIV>BA</RIV> <FORD0>10000</FORD0> <FORD1>10100</FORD1> <FORD2>10103</FORD2>    <reportyear>2025</reportyear>      <num_of_auth>2</num_of_auth>  <inst_support> RVO:67985556 </inst_support>  <permalink>https://hdl.handle.net/11104/0359706</permalink>  <cooperation> <ARLID>cav_un_auth*0359004</ARLID> <name>IES FSV UK</name> <country>CZ</country> </cooperation>  <confidential>S</confidential>  <unknown tag="mrcbC91"> A </unknown>         <unknown tag="mrcbT16-e">ECONOMICS</unknown> <unknown tag="mrcbT16-f">0.4</unknown> <unknown tag="mrcbT16-g">0</unknown> <unknown tag="mrcbT16-h">6</unknown> <unknown tag="mrcbT16-i">0.00006</unknown> <unknown tag="mrcbT16-j">0.049</unknown> <unknown tag="mrcbT16-k">137</unknown> <unknown tag="mrcbT16-5">0.300</unknown> <unknown tag="mrcbT16-6">27</unknown> <unknown tag="mrcbT16-7">Q4</unknown> <unknown tag="mrcbT16-C">10.9</unknown> <unknown tag="mrcbT16-M">0.1</unknown> <unknown tag="mrcbT16-N">Q4</unknown> <unknown tag="mrcbT16-P">10.9</unknown> <arlyear>2024</arlyear>       <unknown tag="mrcbU14"> SCOPUS </unknown> <unknown tag="mrcbU24"> PUBMED </unknown> <unknown tag="mrcbU34"> 001250095200001 WOS </unknown> <unknown tag="mrcbU63"> cav_un_epca*0595822 Ekonomski Vjesnik 37 1 2024 139 150 0353-359X 1847-2206 </unknown> </cas_special> </bibitem>