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- W1515023923 abstract "Recently, Gregorio and Oliveira developed a proximal point scalarization method (applied to multi-objective optimization problems) for an abstract strict scalar representation with a variant of the logarithmic-quadratic function of Auslender et?al. as regularization. In this study, a variation of this method is proposed, using the regularization with logarithm and quasi-distance. By restricting it to a certain class of quasi-distances that are Lipschitz continuous and coercive in any of their arguments, we show that any sequence { ( x k , z k ) } ? R n × R + + m generated by the method satisfies: {zk} is convergent; and {xk} is bounded and its accumulation points are weak Pareto solutions of the unconstrained multi-objective optimization problem" @default.
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- W1515023923 date "2016-01-01" @default.
- W1515023923 modified "2023-09-22" @default.
- W1515023923 title "Logarithmic quasi-distance proximal point scalarization method for multi-objective programming" @default.
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- W1515023923 doi "https://doi.org/10.1016/j.amc.2015.10.065" @default.
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