This paper addresses the problem of finding an approximation to the minimal element set of the objective space for the class of multiobjective deterministic finite horizon optimal control problems. The objective space is assumed to be partially ordered by a pointed convex cone containing the origin. The approximation procedure consists of a two-step discretization in time and state space. Follo...

This paper considers a capacitated vehicle routing problem with fuzzy random travel time and demand (FRVRP). A chance-constrained multiobjective programming is presented based on fuzzy random theory and converted to a crisp equivalent models under some assumptions. To solve such a multiobjective combinatorial optimization problem, this paper presents a hybrid multiobjective particle swarm optim...

This paper presents a multiobjective continuous covering location problem in fuzzy environment. Because of uncertain covering radius, possibility of covering concept is introduced.Since, the uncertainty may cause risk of uncovering customers; the problemis formulated as a risk management model. The presented model is an extension of the discrete covering location models tocontinuous space. Two ...

Multiobjective optimization is the process of simultaneously optimizing two or more conflicting objectives and is used for solving real-world optimization problems in various fields, from product design to process optimization. One of the most effective ways of solving problems with multiple objectives is to use multiobjective evolutionary algorithms (MOEAs). MOEAs draw inspiration from adaptat...

This paper presents the comparative performance of several surrogate-assisted multiobjective evolutionary algorithms MOEAs for geometrical design of a pin-fin heat sink PFHS . The surrogate-assisted MOEAs are achieved by integrating multiobjective population-based incremental learning PBIL with a quadratic response surface model QRS , a radial-basis function RBF interpolation technique, and a K...

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 ...

Within the past several years, important advances have been made in conditional value-at-risk (CVaR) model in finance engineering. CVaR has superior properties in many respects. But, some practical risk problems, such as lending plan of bank, are multiobjective decision making. So, it is key question to study multiobjective CVaR model. This paper proposes a general multiobjective CVaR model in ...

In this study, a multiobjective optimization is applied to Optimal Power Flow Problem (OPF). To effectively achieve this goal, a Multiobjective Ant Lion algorithm (MOALO) is proposed to find the Pareto optimal front for the multiobjective OPF. The aim of this work is to reach good solutions of Active and Reactive OPF problem by optimizing 4-conflicting objective functions simultaneously. Here a...