Inverse Optimization: Theory and Applications

2021/09/08 by Timothy C. Y. Chan, Rafid Mahmood, Chan, Timothy C. Y. +3 · 10 citations
Computer Science · Mathematics · #Advanced Multi-Objective Optimization Algorithms #Advanced Optimization Algorithms Research #FOS: Mathematics #Optimization and Control (math.OC)

paper · pdf · doi:10.48550/arxiv.2109.03920

openalex publication_date 2021/09/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Inverse optimization describes a process that is the "reverse" of traditional mathematical optimization. Unlike traditional optimization, which seeks to compute optimal decisions given an objective and constraints, inverse optimization takes decisions as input and determines an objective and/or constraints that render these decisions approximately or exactly optimal. In recent years, there has been an explosion of interest in the mathematics and applications of inverse optimization. This paper provides a comprehensive review of both the methodological and application-oriented literature in inverse optimization.

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• Inverse Behavioral Optimization of QALY-Based Incentive Systems Quantifying the System Impact of Adaptive Health Programs
• Inverse Mixed-Integer Programming: Learning Constraints then Objective Functions
• Profit Maximization for a Robotics-as-a-Service Model
• Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)
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