Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem

Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem

This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignme...

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Bibliographic Details
Main Authors: LINDAWATI, Linda, Yuan, Zhi, LAU, Hoong Chuin, ZHU, Feida
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
Subjects:
automated parameter tuning
instance-specific parameter configuration
parameter search space reduction
large instance parameter tuning
Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/1657
https://ink.library.smu.edu.sg/context/sis_research/article/2656/viewcontent/Lindawati_Yuan_Lau_Zhu_Automated_20Parameter_20Tuning.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignment Problem (QAP) and show that our framework provides a significant improvement on solutions qualities with much smaller tuning computational time.

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