An Active-Set-Based Recursive Approach for Solving Convex Isotonic Regression with Generalized Order Restrictions
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Published:2023-08-01
Issue:
Volume:
Page:
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ISSN:0217-5959
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Container-title:Asia-Pacific Journal of Operational Research
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language:en
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Short-container-title:Asia Pac. J. Oper. Res.
Author:
Chen Xuyu1,
Li Xudong2,
Su Yangfeng1
Affiliation:
1. School of Mathematical Sciences, Fudan University, Shanghai 200433, P. R. China
2. School of Data Science, Fudan University, Shanghai 200433, P. R. China
Abstract
This paper studies the convex isotonic regression with generalized order restrictions induced by a directed tree. The proposed model covers various intriguing optimization problems with shape or order restrictions, including the generalized nearly isotonic optimization and the total variation on a tree. Inspired by the success of the pool-adjacent-violator algorithm and its active-set interpretation, we propose an active-set-based recursive approach for solving the underlying model. Unlike the brute-force approach that traverses an exponential number of possible active-set combinations, our algorithm has a polynomial time computational complexity under mild assumptions.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Young Elite Scientists Sponsorship Program by CAST
Shanghai Education Development Foundation and Shanghai Municipal Education Commission
Shanghai Science and Technology Program
Publisher
World Scientific Pub Co Pte Ltd
Subject
Management Science and Operations Research,Management Science and Operations Research