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    <title>topic Re: A variable that can be zero or a non-zero range in Mathematical Optimization, Discrete-Event Simulation, and OR</title>
    <link>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404217#M2006</link>
    <description>&lt;P&gt;To model such a semi-continuous variable y, introduce a binary variable x and the following linear constraints:&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;y &amp;gt;= 500*x&lt;/LI&gt;
&lt;LI&gt;y &amp;lt;= 1500*x&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;If x = 0, then y = 0.&amp;nbsp; If x = 1, then y is in [500, 1500].&lt;/P&gt;</description>
    <pubDate>Sat, 14 Oct 2017 15:26:47 GMT</pubDate>
    <dc:creator>RobPratt</dc:creator>
    <dc:date>2017-10-14T15:26:47Z</dc:date>
    <item>
      <title>A variable that can be zero or a non-zero range</title>
      <link>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404202#M2004</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;We are trying to solve an optimization case and now face some problem. It is like follows: We have a variable (water flow at a valve); it can be either zero (when the valve is closed), or between 500-1500 m3/h (when it is open). In the beginning we took the flow as x1*x2, where x1 is binary and x2 is between 500 and 1500. But then SAS can't solve this non-linear thing with binary variable. How can I avoid this situation and linearize this?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks.&lt;/P&gt;</description>
      <pubDate>Sat, 14 Oct 2017 10:27:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404202#M2004</guid>
      <dc:creator>grandmoon</dc:creator>
      <dc:date>2017-10-14T10:27:05Z</dc:date>
    </item>
    <item>
      <title>Re: A variable that can be zero or a non-zero range</title>
      <link>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404211#M2005</link>
      <description>&lt;P&gt;Maybe you could try Genetic Algorithm .&lt;/P&gt;
&lt;P&gt;Can you explain it more,and better post an example .&lt;/P&gt;</description>
      <pubDate>Sat, 14 Oct 2017 11:41:24 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404211#M2005</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2017-10-14T11:41:24Z</dc:date>
    </item>
    <item>
      <title>Re: A variable that can be zero or a non-zero range</title>
      <link>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404217#M2006</link>
      <description>&lt;P&gt;To model such a semi-continuous variable y, introduce a binary variable x and the following linear constraints:&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;y &amp;gt;= 500*x&lt;/LI&gt;
&lt;LI&gt;y &amp;lt;= 1500*x&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;If x = 0, then y = 0.&amp;nbsp; If x = 1, then y is in [500, 1500].&lt;/P&gt;</description>
      <pubDate>Sat, 14 Oct 2017 15:26:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Mathematical-Optimization/A-variable-that-can-be-zero-or-a-non-zero-range/m-p/404217#M2006</guid>
      <dc:creator>RobPratt</dc:creator>
      <dc:date>2017-10-14T15:26:47Z</dc:date>
    </item>
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