We introduce and analyze a novel scalarization technique and an associated algorithm for generating an approximation of the Pareto front (i.e., the efficient set) of nonlinear multiobjective optimization problems. Our approach is applicable to nonconvex problems, in particular to those with disconnected Pareto fronts and disconnected domains (i.e., disconnected feasible sets). We establish the ...

This paper presents a new method for the numerical solution of nonlinear multiobjective optimization problems with an arbitrary partial ordering in the objective space induced by a closed pointed convex cone. This algorithm is based on the well-known scalarization approach by Pascoletti and Serafini and adaptively controls the scalarization parameters using new sensitivity results. The computed...

‎A common approach to determine efficient solutions of a multiple objective optimization problem‎ ‎is reformulating it to a parameter dependent scalar optimization problem‎. ‎This reformulation is called scalarization approach‎. Here, a well-known scalarization approach named Pascoletti-Serafini scalarization is considered‎. First, some difficulties of this scalarization are discussed and then ...

‎a common approach to determine efficient solutions of a multiple objective optimization problem‎ ‎is reformulating it to a parameter dependent scalar optimization problem‎. ‎this reformulation is called scalarization approach‎. here, a well-known scalarization approach named pascoletti-serafini scalarization is considered‎. first, some difficulties of this scalarization are discussed and then ...

We propose an algorithm to generate inner and outer polyhedral approximations the upper image of a bounded convex vector optimization problem. It is approximation based on solving norm-minimizing scalarizations. Unlike Pascoletti–Serafini scalarization used in literature for similar purposes, it does not involve direction parameter. Therefore, free direction-biasedness. also modification by int...

Generally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of electricity consumption cost, value from external power grid, and peak load smoothing. All these objectives desirable a building, however, related works, just one mentioned considered investigated. In this work, aut...

In this study, we present a general framework of outer approximation algorithms to solve convex vector optimization problems, in which the Pascoletti-Serafini (PS) scalarization is solved iteratively. This finds minimum ‘distance’ from reference point, usually taken as vertex current approximation, upper image through given direction. We propose efficient methods select parameters (the point an...

We propose an exact algorithm for solving biobjective integer programming problems, which arise in various applications of operations research. The is based on Pascoletti-Serafini scalarizations to search specified regions (boxes) the objective space and returns set nondominated points. implement with different strategies, where choices scalarization model parameters splitting rule differ. then...