Having the possibility to systematically evaluate objectives of different nature at the same time is becoming crucial to operate processes, plants and production sites under more sustainable conditions. Most often, this multi-objective nature is tackled by combining all individual objectives into a global Weighted Sum (WS). This approach is widespread because it is easy to use and understand, b...

The corridor allocation problem (CAP) seeks the effective placement of given facilities in two parallel rows on opposite sides of a central corridor. The placement of the facilities in both the rows starts from the same level and no gap is allowed between two facilities of a row. The CAP is formulated here as a nonlinear bi-objective optimization problem, in which both the overall flow cost amo...

Secondary pollution derives from complex non-linear reactions involving precursor emissions, namely VOC, NOx, NH3, primary PM and SO2. Due to difficulty to cope with this complexity, Decision Support Systems (DSSs) are key tools to support Environmental Authorities in planning cost-effective air quality policies that fulfill EU Directive 2008/50 requirements. The objective of this work is to fo...

We give an introduction to nonlinear multiobjective optimization by covering some basic concepts as well as outlines of some methods. Because Pareto optimal solutions cannot be ordered completely, we need extra preference information coming from a decision maker to be able to select the most preferred solution for a problem involving multiple conflicting objectives. Multiobjective optimization ...

We describe the development and testing of a metaheuristic procedure, based on the scatter search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of ...

We describe the development and testing of a metaheuristic procedure, based on the scatter search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of ...

The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Object...

The objective of this paper is to give an overview of the optimization strategies that are required when designing chemical processes in which the existence of regions of feasible steady-state operation must be ensured in the face of parameter variations. Two major areas are considered: optimal design with a fixed degree of flexibility, and design with optimal degree of flexibility. For the fir...

In this paper, we prove a nonlinear separation associated with a constrained multiobjective optimization problem in the image space, as well as the equivalence between the existence of nonlinear separation function and a saddle point condition for a generalized Lagrangian function associated with the given problem. As applications, we obtain some equivalent conditions on exact penalty methods f...

In this paper, we propose a nonlinear multi-objective optimization problem whose parameters in the objective functions and constraints vary in between some lower and upper bounds. Existence of the efficient solution of this model is studied and gradient based as well as gradient free optimality conditions are derived. The theoretical developments are illustrated through numerical examples.