A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced...

In this paper, by virtue of a nonlinear scalarization function, two nonlinear weak separation functions, a nonlinear regular weak separation function, and a nonlinear strong separation function are first introduced, respectively. Then, by the image space analysis, a global saddle-point condition for a nonlinear function is investigated. It is shown that the existence of a saddle point is equiva...

In this paper we consider a vector optimization problem; we present some scalarization techniques for finding all the vector optimal points of this problem and we discuss the relationships between these methods. Moreover, in the linear case, the study of dual variables is carried on by means of sensitivity analysis and also by a parametric approach. We also give an interpretation of the dual va...

a problem that sometimes occurs in multiobjective optimization is the existence of a large set of fairly effcient solutions. hence, the decision making based on selecting a unique preferred solution is diffcult. considering models with fair b-effciency relieves some of the burden from the decision maker by shrinking the solution set, since the set of fairly b-efficient solutions is contained with...

Comment on: [18F]Fluoro-Deoxy-Glucose positron emission tomography to evaluate lymph node involvement in patients with muscle-invasive bladder cancer receiving neoadjuvant pembrolizumab. Marandino L, Capozza A, Bandini M, Raggi D, Fare E, Pederzoli F, Gallina Capitanio U, Bianchi Gandaglia G, Fossati N, Colecchia Giannatempo P, Serafini Padovano B, Salonia Briganti Montorsi Alessi Necchi ...

Abstract In this paper we present results on dynamic multivariate scalar risk measures, which arise in markets with transaction costs and systemic risk. Dual representations of such measures are presented. These then used to obtain the main time consistency; namely, an equivalent recursive formulation multiportfolio consistency. We motivated study consistency as superhedging measure (with a sin...

The decomposition-based multi-objective evolutionary algorithm (MOEA/D) transforms a optimization problem (MOP) into set of single-objective subproblems for collaborative optimization. Mismatches between and solutions can lead to severe performance degradation MOEA/D. Most existing mismatch coping strategies only work when the L∞ scalarization is used. A strategy that use any Lp scalarization, ...