Electric vehicles (EVs) are the most promising future transportation system, and most of the
public and private combustion vehicles used are already being replaced by them. In any …

Scalarization is a common technique to transform a multiobjective optimization problem into
a scalar-valued optimization problem. This article deals with the weighted Tchebycheff …

Within the current literature on multi-objective optimization, there is a scarcity of comparisons
between equation-based white-box solvers to evolutionary black-box solvers. It is commonly …

In this paper, we present an outer approximation algorithm for computing the Edgeworth–
Pareto hull of multi-objective mixed-integer linear programming problems (MOMILPs). It …

Convex approximation sets for multiobjective optimization problems are a well-studied
relaxation of the common notion of approximation sets. Instead of approximating each image …

The nondominated set of a multiple objective discrete optimization problem is known to
contain unsupported nondominated points, which outnumber the supported ones and are …

Many solution algorithms for multiobjective optimization problems are based on
scalarization methods that transform the multiobjective problem into a scalar-valued …

Linear-parametric optimization, where multiple objectives are combined into a single
objective using linear combinations with parameters as coefficients, has numerous links to …

In this paper, we present the first outer approximation algorithm for multi-objective mixed-
integer linear programming problems with any number of objectives. The algorithm also …

The increased flexibility provided by the MOO framework also raises the question of what
constitutes a solution to it. The definition of optimality is no longer valid, as each objective …