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 <datafield tag="088" ind1="" ind2="">
  <subfield code="a">2021Luxembourg</subfield> 
  </datafield>
<datafield tag="909" ind1="C" ind2="0">
<subfield code="p">TRANSP-OR</subfield>
</datafield>
<datafield tag="980" ind1="" ind2="">
<subfield code="a">TALK</subfield>
</datafield>
 <datafield tag="700" ind1="" ind2="">
  <subfield code="a">Pougala, Janody</subfield> 
  </datafield>
 <datafield tag="700" ind1="" ind2="">
  <subfield code="a">Hillel, Tim</subfield> 
  </datafield>
 <datafield tag="700" ind1="" ind2="">
  <subfield code="a">Bierlaire, Michel</subfield> 
  </datafield>
<datafield tag="245" ind1="" ind2="">
<subfield code="a">
Reconstructing daily schedules of individuals: a utility maximization approach</subfield>
</datafield>
<datafield tag="260" ind1="" ind2="">
<subfield code="c">2021</subfield>
</datafield>
<datafield tag="711" ind1="2" ind2="">
<subfield code="a">
Lunch Seminar in Economics</subfield>
<subfield code="c">
Department of Economics and Management, University of Luxembourg , Luxembourg</subfield>
<subfield code="d">May 05, 2021</subfield>
</datafield>
<datafield tag="520" ind1="" ind2="">
<subfield code="a">
The understanding and prediction of daily activity patterns is important to understand the use of resources such as transportation and energy. In this presentation, we propose a modeling approach based on utility maximization.  We assume that an individual schedules her day in order to maximize her overall utility. To do so, she solves a mixed integer optimization problem which combines discrete decisions, such as whether or not to participate in different activities, and continuous decisions, such as the start times and duration of planned activities. We propose a detailed specification of the optimization problem, illustrate it on concrete examples, and discuss how the model  parameters can be calibrated from real-world data.</subfield>
</datafield>
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