In this work nonlinear non-convex multiobjective bilevel optimization problems are discussed using an optimistic approach. It is shown that the set of feasible points of the upper level function, the so-called induced set, can be expressed as the set of minimal solutions of a multiobjective optimization problem. This artificial problem is solved by using a scalarization approach by Pascoletti a...

In this paper, we investigate the distributed power allocation for multi-cell OFDMA networks taking both energy efficiency and inter-cell interference (ICI) mitigation into account. A performance metric termed as throughput contribution is exploited to measure how ICI is effectively coordinated. To achieve a distributed power allocation scheme for each base station (BS), the throughput contribu...

In managerial and economic applications, there appear problems in which the goal is to simultaneously optimize several criteria functions (CFs). However, since the CFs are in conflict with each other in such cases, there is not a feasible point available at which all CFs could be optimized simultaneously. Thus, in such cases, a set of points, referred to as 'non-dominate' points (NDPs), will be...

A general duality framework in convex multiobjective optimization is established using the scalarization with K-strongly increasing functions and the conjugate duality for composed convex cone-constrained optimization problems. Other scalarizations used in the literature arise as particular cases and the general duality is specialized for some of them, namely linear scalarization, maximum(-line...

The paper presents main features of the conic scalarization method in multiobjective optimization. The conic scalarization method guarantee to generate all proper efficient solutions and does not require any kind of cenvexity or boundedness conditions. In addition the preference and reference point information of the decision maker is taken into consideretion by this method. Also in this paper,...

Pavlos Paraskevopoulos University of Trento, Italy, Telecom Italia SKIL [email protected] Thanh-Cong Dinh University of Trento, Italy, Telecom Italia SKIL [email protected] Zolzaya Dashdorj University of Trento, Italy, Telecom Italia SKIL, Fondazione Bruno Kessler [email protected] Themis Palpanas University of Trento, Italy, [email protected] Luciano Serafini Fondazione ...

Almost a year has passed since the death of italo Serafini but his memory lives on. in fact, having got over the emotional distress coming from his demise, that seemed unacceptable even though inevitable, we can now sedately pay homage to him as a maestro, colleague and friend. There can be no doubt that professionally he gave infinitely more than he received. For years he was the pre-eminent i...

In multi-objective reinforcement learning (MORL) the agent is provided with multiple feedback signals when performing an action. These signals can be independent, complementary or conflicting. Hence, MORL is the process of learning policies that optimize multiple criteria simultaneously. In this abstract, we briefly describe our extensions to single-objective multi-armed bandits and reinforceme...

Scalarization approaches are the simplest methods for solving the multiobjective problems. The idea of scalarization is based on decomposition of multiobjective problems into single objective sub-problems. Every one of these sub-problems can be solved in a parallel manner since they are independent with each other. Hence, as a scalarization approach, systematically modification on the desirabil...