Deriving efficient variants in complex multiple criteria decision making problems requires optimization. This hampers greatly broad use of any multiple criteria decision making method. In multiple criteria decision making Pareto sets, i.e. sets of efficient vectors of criteria values corresponding to feasible decision alternatives, are of primal interest. Recently, methods have been proposed to...

Evolutionary Algorithms are a standard tool for multi-objective optimization that are able to approximate the Pareto front in a single optimization run. However, for some selection operators, the algorithm stagnates at a certain distance from the Pareto front without convergence for further iterations. We analyze this observation for different multi-objective selection operators. We derive a si...

This paper presents results of extensive computational experiments in which evolutionary multiobjective algorithms were used to find Pareto-optimal solutions to a complex structural design problem. In particular, Strength-Pareto Evolutionary Algorithm 2 (SPEA2) was combined with a mathematical programming method to find optimal designs of steel structural systems in tall buildings with respect ...

Title: Analysis of manufacturing supply chains using system dynamics and multi-objective optimization I ABSTRACT Supply chains are in general complex networks composed of autonomous entities whereby multiple performance measures in different levels, which in most cases are in conflict with each other, have to be taken into account. Hence, due to these multiple performance measures, supply chain...

This paper describes an application of Adaptive Range Multiobjective Genetic Algorithms (ARMOGAs) to aerodynamic wing optimization. The objectives are to minimize transonic and supersonic drag coefficients, as well as the bending and twisting moments of the wings for the supersonic airplane. A total of 72 design variables are categorized to describe the wing’s planform, thickness distribution, ...

Modern drug discovery involves the simultaneous optimization of many physicochemical and biological properties that transcends the historical focus on bioactivity alone. The process of resolving many requirements is termed 'multi-objective optimization', and here we discuss how this can be used for drug discovery, focusing on evolutionary molecule design to incorporate optimal predicted absorpt...

This paper presents a multi-objective optimal power flow technique using particle swarm optimization. Two conflicting objectives, generation cost, and environmental pollution are minimized simultaneously. A multiobjective particle swarm optimization method is used to solve this highly nonlinear and non-convex optimization problem. A diversity preserving technique is incorporated to generate eve...

This paper presents the strategy for multi-criteria optimization of a prototype. There are taken into account two different optimization criteria. An original computer program was made to make possible the graphic display of regions on the 3D model surface, which exceed a limit for surface roughness, initial established. The computer program allows the automate calculation of optimal position f...

We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachytherapy. The optimization considers up to 300 parameters. The objectives are expressed in terms of statistical parameters, from dose distributions. These parameters are approximated from dose values from a small number of p...

The optimization of multimodal functions is a challenging task, in particular when derivatives are not available for use. Recently, in a directional direct search framework, a clever multistart strategy was proposed for global derivative-free optimization of single objective functions. The goal of the current work is to generalize this approach to the computation of global Pareto fronts for mul...