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Exact algorithms for multi-objective integer non-linear programming by cutting solution space

机译:通过削减解空间实现多目标整数非线性规划的精确算法

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Multi-objective integer non-linear programming (MINP) problems are ubiquitous in real life, however, only the ε-constraint method can be used to solve MINP problems. To improve the computation time of the ε-constraint method, we propose improved exact algorithms to obtain all the Pareto-optimal solutions for MINP. Our contribution is to cut most non-Pareto-optimal solutions by several specific Pareto-optimal solutions before performing ε-constraint method. Thus, the computation time can be significantly saved. The performance of these exact algorithms are evaluated by the general instances of the multi-objective assignment problem. The computational results show that the performance of the proposed exact algorithms are better than the ε-constraint method.
机译:多目标整数非线性规划(MINP)问题在现实生活中无处不在,但是,只有ε约束方法可以用来解决MINP问题。为了提高ε约束方法的计算时间,我们提出了改进的精确算法,以获取MINP的所有Pareto最优解。我们的贡献是在执行ε约束方法之前,通过几个特定的​​Pareto最优解来削减大多数非Pareto最优解。因此,可以大大节省计算时间。这些精确算法的性能通过多目标分配问题的一般实例进行评估。计算结果表明,所提出的精确算法的性能优于ε约束方法。

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