In this paper, we focus on expensive multiobjective optimization problems and propose a method to predict an approximation of the Pareto optimal set using classification of sampled decision vectors as dominated or nondominated. The performance of our method, called EPIC, is demonstrated on a set of benchmark problems used in the multiobjective optimization literature and compared with state-of ...

The nondominated frontier of a multiobjective optimization problem can be overwhelming to a decision maker, as it is often either exponential or infinite in size. Instead, a representation of this set in the form of a small sample of points is often preferred. In this paper we present a new biobjective criterion space search method for generating a small set of equidistant points based on the s...

We give explicit solutions for utility optimization problems in the presence of Knightian uncertainty in continuous time. We solve the robust optimization problem explicitly both when the investor’s utility is of CRRA and of CARA type. We show that our problem formulation allows us to apply Sion’s min max theorem and to solve the dual problem explicitly. Mathematics Subject Classification: 91B2...

we consider biobjective shortest path problems in networks with fuzzy arc lengths. considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective prob- lems. the rst and second approaches are extensions of the labeling method to solve the sing...

Assessing the performance of Pareto front (PF) approximations is a key issue in field evolutionary multi/many-objective optimization. Inverted generational distance (IGD) has been widely accepted as indicator for evaluating comprehensive quality PF approximation. However, IGD usually becomes infeasible when facing real-world optimization problem it needs to know true priori. In addition, time c...

We consider the bicriterion multimodal assignment problem, which is a new generalization of the classical linear assignment problem. A two-phase solution method using an effective ranking scheme is presented. The algorithm is valid for generating all nondominated criterion points or an approximation. Extensive computational results are conducted on a large library of test instances to test the ...

The paper considers multi-criteria dynamic decision process. We focus on the efficient realizations of the dynamic process which are characterized by nondominated values of the multi-period criteria function. The aim of the paper is to use the compromise hypersphere method to rank the efficient realizations. The presented method allows us to take into account the risk aversion of the decision m...

In this paper, we propose near admissible multiobjective search algorithms to approximate, with performance guarantee, the set of Pareto optimal solution paths in a state space graph. Approximation of Pareto optimality relies on the use of an epsilon-dominance relation between vectors, significantly narrowing the set of nondominated solutions. We establish correctness of the proposed algorithms...