problems, multi-objective branch and bound methods are only rarely applied compared to the predominant objective space methods …. In this paper we propose modifications to increase the performance of multi-objective branch and bound algorithms by … bound set to implement a multi-objective best-first strategy. By adaptively solving scalarizations in the root node to …

multi-objective model formulation and decision-making framework of the stochastic capacitated lot sizing problem (MOSCLSP … sequential market observations. We propose an interactive multi-objective optimization algorithm for solving the MO-SCLSP, that … multi-objective optimization are applied to derive a set of Pareto-optimal solutions. These Pareto-optimal solutions outline …

multi-objective model formulation and decision-making framework of the stochastic capacitated lot sizing problem (MOSCLSP … sequential market observations. We propose an interactive multi-objective optimization algorithm for solving the MO-SCLSP, that … multi-objective optimization are applied to derive a set of Pareto-optimal solutions. These Pareto-optimal solutions outline …

production systems among smaller companies to compensate for their production deficiencies. This study proposes a multi-objective … from the machine learning model equals 0.9977, indicating this method's high accuracy and efficiency. The Lp-Metric, multi-objective …

This study introduces a hybrid feature selection technique with a multi-objective algorithm incorporating Information … different multi-objective feature selection techniques on five different high-dimensional datasets. Our proposed model …

, specifically flash floods triggered by cloudburst events. We propose a multi-objective supply chain model that minimizes both cost …