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DTSTART:20251026T030000
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UID:calendar.29368.field_data.0@www.u-gov-ricerca.uniroma1.it
DTSTAMP:20260405T115723Z
CREATED:20250530T083650Z
DESCRIPTION:AbstractDecision-making in real-world applications often involv
 es multiple competing objectives\, with decision-makers applying their own
  preferences to balance trade-offs. Inverse Multiobjective Optimization (I
 MO) aims to infer both the underlying objective functions and the implicit
  preferences that drive observed decisions. In this work\, we propose a no
 vel approach that integrates clustering into inverse optimization to group
  decision-makers based on their preference structures rather than their ob
 served decisions. Our method is an optimization-based clustering IMO frame
 work that minimizes optimality gaps ―the difference between the objective 
 value of observed decisions and the optimal value under the inferred prefe
 rence structure―\, resulting in Mixed-Integer Quadratic Programs (MIQPs). 
 To enhance computational efficiency\, we derive a heuristic that provides 
 a warm-start solution for the global optimization models\, improving conve
 rgence and solution quality. Additionally\, we incorporate interpretabilit
 y requirements to ensure that inferred preferences are meaningful and alig
 n with domain knowledge. We validate our approach with computational exper
 iments on a real-world diet recommendation problem\, demonstrating its abi
 lity to uncover interpretable and robust decision-making patterns. Nuria i
 s a PhD Student at Department of Statistics and Operations Research\, Facu
 lty of Mathematics\, University of Seville(IMUS).
DTSTART;TZID=Europe/Paris:20250618T143000
DTEND;TZID=Europe/Paris:20250618T143000
LAST-MODIFIED:20250530T113126Z
LOCATION:Room A5 DIAG
SUMMARY:Preference Estimation in Inverse Multiobjective Optimization - Nuri
 a Gómez Vargas
URL;TYPE=URI:http://www.u-gov-ricerca.uniroma1.it/node/29368
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