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Showing 1 to 6 of 6 for “"Pareto sets"”.
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Efficient Continuous Pareto Exploration in Multi-Task Learning
… exists. Recent papers introduced the concept of Pareto optimality to this field and directly cast multi-task learning as multiobjective optimization problems, but solutions returned by existing methods are typically finite, sparse, and discrete. We present a novel, efficient method that generates …
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Using metaheuristics with the ranking and selection indifference-zone procedure MMY in problems with many objectives
… in exploring these spaces and approximating Pareto-optimal solutions, they lack statistical guarantees, making the reliability of their outputs uncertain. In contrast, ranking and selection (R&S) procedures provide statistical guarantees, specifically for the probability of correct selection …
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Asteroid hazard mitigation: deflection models and mission analysis
… optimization is then used to construct a set of Pareto-optimal asteroid deflection missions. The Pareto-optimality is here achieved not only by maximizing the deflection of the threatening object, but also by minimizing the total mass of the deflection mission at launch and the warning time …
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Approximation of Multiobjective Optimization Problems
… objectives. This is captured by the tradeoff or Pareto curve, the set of all feasible solutions whose vector of the various objectives is not dominated by any other solution. Typically, we have a small number of objectives and we wish to plot the tradeoff curve to get a sense of the design space. …
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Strategies for Effective Mitigation of Infectious Diseases, with Focus on COVID-19
… efforts. We establish structural properties of Pareto sets of strategies and analyze how they adjust with community characteristics, leading to key insights. Our findings offer actionable strategies for diverse communities and underscore the substantial value of tailoring mitigation efforts to …
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Modelling and Multi-objective Optimization of Continuous Protein Recovery in Liquid-Solid Circulating Fluidized Bed (LSCFB)
… problems. The optimization resulted in Pareto optimal solutions, which provides a broad range of non-dominated solutions due to conflicting behaviour of the operating and design parameters on the system performance indicators such as the protein production rate, the percent recovery and …