Our goal in this work is to develop analytical tools to support the definition of balanced and compatible sets of vehicle specifications in the early stages of vehicle development. In this paper, we discuss the development and application of a Technical Feasibility Model (TFM) that may be used in preliminary design to assess the technical feasibility and optimality of specified combinations of ...

We consider the problem of approximating the Pareto set of convex multicriteria optimization problems by a discrete set of points and their convex combinations. Finding the scalarization parameters that maximize the improvement in bound on the approximation error when generating a single Pareto optimal solution is a nonconvex optimization problem. This problem is solvable by enumerative techniq...

In this research report, the author proposes two new evolutionary approaches to Multiobjective Optimization Problems (MOPs)— Dynamic Particle Swarm Optimization (DPSMO) and Dynamic Particle Swarm Evolutionary Algorithm (DPSEA). In DPSMO, instead of using genetic operators (e.g., crossover and mutation), the information sharing technique in Particle Swarm Optimization is applied to inform the en...

Recent studies confront the problem of multiple error terms through summation. However this implicitly assumes prior knowledge of the problem's error surface. This study constructs a population of Pareto optimal Neural Network regression models to describe a market generation process in relation to the forecasting of its risk and return.

A core challenge ofMultiobjective Evolutionary Algorithms (MOEAs) is to attain evenly distributed Pareto optimal solutions along the Pareto front. In this paper, we propose a novel asymmetric Pareto-adaptive (apa) scheme for the identification of well distributed Pareto optimal solutions based on the geometrical characteristics of the Pareto front. The apa scheme applies to problem with symmetr...

Optimization of grinding process is a multiobjective optimization problem. However, it traditionally has been solved as a single objective problem. In this paper, general, useful and practical multidisciplinary optimization methods are discussed for optimal design of surface grinding processes. The methods allow designer to explicitly consider and control multiple design objectives as an integr...

‎the aim of this paper is to study distribution of ratios of generalized order statistics from pareto distribution. parameter estimation of pareto distribution based on generalized order statistics and ratios of them have been obtained. inferences using method of moments and unbiased estimator have been obtained to develop point estimations. consistency of unbiased estimator has been illustrate...