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Quadratic convex reformulations for multiObjective binary quadratic programming
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DOI：10.1007/s10898-025-01586-2.png)
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Abstract
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Multiobjective binary quadratic programming refers to optimization problems involving multiple quadratic-potentially non-convex-objective functions and a feasible set that includes binary constraints on the variables. In this paper, we extend the well-established Quadratic Convex Reformulation technique, originally developed for single-objective binary quadratic programs, to the multiobjective setting. We propose a branch-and-bound algorithm where lower bound sets are derived from properly defined quadratic convex subproblems. Computational experiments on multiobjective k-item Quadratic Knapsack and multiobjective Max-Cut instances demonstrate the effectiveness of our approach.
Keywords:
Multiobjective Optimization
Binary Quadratic Problems
Quadratic Convex Reformulations
Branch-and-Bound algorithm
Journal
J
IF:
1.7
Papers:
88
Citations:
6.9K
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