This paper deals with biobjective combinatorialoptimization problems where both objectives are required to be well-balanced. Lorenz dominance is a refinement of the Pareto dominance that has been proposed in economic...
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ISBN:
(纸本)9783319231143;9783319231136
This paper deals with biobjective combinatorialoptimization problems where both objectives are required to be well-balanced. Lorenz dominance is a refinement of the Pareto dominance that has been proposed in economics to measure the inequalities in income distributions. We consider in this work the problem of computing the Lorenz optimal solutions to combinatorialoptimization problems where solutions are evaluated by a two-component vector. This setting can encompass fair optimization or robust optimization. The computation of Lorenz optimal solutions in biobjective combinatorialoptimization is however challenging (it has been shown intractable and NP-hard on certain problems). Nevertheless, to our knowledge, very few works address this problem. We propose thus in this work new methods to generate Lorenz optimal solutions. More precisely, we consider the adaptation of the well-known two-phase method proposed in biobjective optimization for computing Pareto optimal solutions to the direct computing of Lorenz optimal solutions. We show that some properties of the Lorenz dominance can provide a more efficient variant of the two-phase method. The results of the new method are compared to state-of-the-art methods on various biobjective combinatorialoptimization problems and we show that the new method is more efficient in a majority of cases.
This paper tackles the multiobjective controller placement problem in Software Defined Networks (SDN), a complex optimization challenge affecting network Quality of Service (QoS). In contrast to prior approaches focus...
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Security issues in information management are increasingly moving towards the centre of corporate interests. This paper presents a multiobjective modelling approach that interactively assists IT managers in their atte...
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Security issues in information management are increasingly moving towards the centre of corporate interests. This paper presents a multiobjective modelling approach that interactively assists IT managers in their attempts to reduce a given risk by evaluating and selecting portfolios (i.e. bundles) of security measures. The proposed multi-step procedure identifies attractive portfolio candidates and finally establishes the "best" one with respect to the decision-maker's preferences. Our model and its possible application are demonstrated by means of a numerical example based on real-world data that evaluates the risk of hacking faced by a Local Area Network in an academic environment.
Flow-shop scheduling problems are generally studied in a single-objective deterministic way whereas they are multiobjective and are subjected to a wide range of *** evolutionary algorithms are commonly used to solve m...
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Flow-shop scheduling problems are generally studied in a single-objective deterministic way whereas they are multiobjective and are subjected to a wide range of *** evolutionary algorithms are commonly used to solve multiobjective and stochastic problems,very few approaches combine simultaneously these two *** the paper the multiobjective flow shop scheduling problem is modeled with the stochastic processing time and the machine breakdown.A mathematical scheme is designed for the largest flow of time and the largest delay time.A hybrid multiobjective genetic algorithm is proposed to solve the optimization problems iteratively on uncertain *** results of simulation experiments are shown that the algorithm can provide a good performance for the flow shop scheduling problems on the uncertain condition.
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