Solving bi-objective unconstrained binary quadratic programming problem with multi-objective path relinking algorithm

This paper investigates a multi-objective path relinking algorithm in order to optimize a bi-objective unconstrained binary quadratic programming problem. In this algorithm, we integrate the path relinking techniques into hypervolume-based multi-objective optimization, where we propose a method to g...

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Bibliographic Details
Published in:2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) pp. 289 - 293
Main Authors: Lei Song, Rong-Qiang Zeng, Yang Wang, Ming-Sheng Shang
Format: Conference Proceeding
Language:English
Published: IEEE 01.08.2016
Subjects:
Approximation algorithms
hypervolume contribution
local search
multi-objective optimization
Pareto optimization
path relinking
Quadratic programming
Search problems
Sociology
unconstrained binary quadratic programming problem
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Summary:This paper investigates a multi-objective path relinking algorithm in order to optimize a bi-objective unconstrained binary quadratic programming problem. In this algorithm, we integrate the path relinking techniques into hypervolume-based multi-objective optimization, where we propose a method to generate a path and select a set of non-dominated solutions from the generated path for further improvements. Experimental results show that the proposed algorithm is very effective compared with the original multi-objective optimization algorithms.
DOI:10.1109/FSKD.2016.7603188