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An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadratic Programming Problem

机译:一种有效的遗传算法,具有统一交叉的双目标无约束二元二元规划问题

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The unconstrained binary quadratic programming problem is one of the most studied NP-hard problem with its various practical applications. In this paper, we propose an effective multi-objective genetic algorithm with uniform crossover for solving bi-objective unconstrained binary quadratic programming problem. In this algorithm, we integrate the uniform crossover within the hypervolume-based multi-objective optimization framework for further improvements. The computational studies on 10 benchmark instances reveal that the proposed algorithm is very effective in comparison with the original multi-objective optimization algorithms.
机译:无约束的二进制二进制编程问题是其各种实际应用中研究的最多的NP难题之一。在本文中,我们提出了一种具有统一交叉的有效多目标遗传算法,用于求解双目标无约束二元规划问题。在该算法中,我们将统一的交叉整合在基于超智能的多目标优化框架内,以进一步改进。关于10个基准实例的计算研究表明,与原始多目标优化算法相比,该算法非常有效。

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