often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. instead it is obtained by some numerical analysis such as fe structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. yet, the numerical analyses are considerably time consuming to obtain the final value of objective functi...

this paper focuses upon the development of an efficient method for conceptual design optimization of a satellite. there are many option for a satellite subsystems that could be choice, as acceptable solution to implement of a space system mission. every option should be assessment based on the different criteria such as cost, mass, reliability and technology contraint (complexity). in this rese...

‎In this paper‎, ‎we propose an algorithm to obtain an approximation set of the (weakly) nondominated points of nonsmooth multiobjective optimization problems with equality and inequality constraints‎. ‎We use an extension of the Wolfe duality to construct the separating hyperplane in Benson's outer algorithm for multiobjective programming problems with subdifferentiable functions‎. ‎We also fo...

Recently, a general-purpose local-search heuristic method called Extremal Optimization (EO) has been successfully applied to some NP-hard combinatorial optimization problems. This paper presents an investigation on EO with its application in multiobjective optimization and proposes a new novel elitist (1+ λ ) multiobjective algorithm, called Multiobjective Extremal Optimization (MOEO). In order...

In this paper, we propose a new multiobjective optimization approach based on the clonal selection principle. Our approach is compared with respect to other evolutionary multiobjective optimization techniques that are representative of the state-of-the-art in the area. In our study, several test functions and metrics commonly adopted in evolutionary multiobjective optimization are used. Our res...

The seminar "Hybrid and Robust Approaches to Multiobjective Optimization" was a sequel to two previous Dagstuhl seminars (04461 in 2004 and 06501 in 2006). The main idea of this seminar series has been to bring together two contemporary elds related to multiobjective optimization Evolutionary Multiobjective Optimization (EMO) and Multiple Criteria Decision Making (MCDM) to discuss critical rese...

The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

The use of Surrogate Based Optimization (SBO) is widely spread in engineering design to reduce the number of computational expensive simulations. However, “real-world” problems often consist of multiple, conflicting objectives leading to a set of competitive solutions (the Pareto front). The objectives are often aggregated into a single cost function to reduce the computational cost, though a b...

This paper presents an optimization strategy for a broke system design and operation in papermaking process. A multiobjective stochastic optimization model is presented featuring (i) a stochastic two-state Markov process based submodel for the broke tower, (ii) an operational submodel for the optimization of the broke dosage, and (iii) a multiobjective design problem. An efficient optimization ...

In this chapter we present a brief analysis of the current research performed on evolutionary multiobjective optimization. After analyzing first and second generation multiobjective evolutionary algorithms, we address two important issues: the role of elitism in evolutionary multiobjective optimization and the way in which concepts from multiobjective optimization can be applied to constraint-h...