Multi-objective integer or mixed-integer programming problems typically have disconnected
feasible domains, making the task of constructing an approximation of the Pareto front …

Dealing with multi-objective problems by using generation methods has some interesting
advantages since it provides the decision-maker with the complete information about the set …

The present research proposes an interactive optimization framework to aid tourists to
organize their trip by generating personalized walking itineraries among several Points of …

In multiobjective optimization, the result of an optimization algorithm is a set of efficient
solutions from which the decision maker selects one. It is common that not all the efficient …

We propose a novel Mixed-Integer Nonlinear Programming (MINLP) model for sparse
optimization based on the polyhedral k-norm. We put special emphasis on the application of …

In this article we introduce an algorithm that approximates the nondominated sets of
multiobjective mixed-integer convex optimization problems. The algorithm constructs an …

We consider split algorithms that partition the objective function space into p or p− 1
dimensional regions so as to search for nondominated points of multiobjective integer …

This work proposes a novel multi-objective optimization approach that globally finds a
representative non-inferior set of solutions, also known as Pareto-optimal solutions, by …

We present a tri-objective mixed-integer linear programming model of the tactical resource
allocation problem with inventories, called the generalized tactical resource allocation …

In this paper, we consider generating a representative subset of nondominated points at a
prespecified precision in multi-objective mixed-integer programs (MOMIPs). The number of …