Search results for "Principle"

Some Advantages of the Gyrotrons with Width Emitters

2020

The main trends in gyrotron development are escalation of the radiated power and increasing the frequency of coherent radiation. For both trends it is beneficial to develop gyrotrons with wide emitters because this allows one to use cryomagnets with smaller inner bore sizes. For analyzing and optimizing the operation of gyrotrons with wide emitters it is proposed to represent such emitters as a superposition of thin rings and analyze the properties of electron beams emitted by each of these rings. The analysis of electron beam properties, for electron optical systems with different emitters is presented. The possibility to reduce velocity spread by anode profiling is discussed. The dynamics…

Density functional theory description of random Cu-Au alloys

2019

Density functional alloy theory is used to accurately describe the three core effects controlling the thermodynamics of random Cu-Au alloys. These three core effects are exchange correlation (XC), ...

Regularization and finite element approximation of the wave equation with Dirichlet boundary data

1990

Interactive Multiobjective Robust Optimization with NIMBUS

2018

In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behavio…

PAINT–SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization

2014

We introduce a novel approximation method for multiobjective optimization problems called PAINT–SiCon. The method can construct consistent parametric representations of Pareto sets, especially for nonconvex problems, by interpolating between nondominated solutions of a given sampling both in the decision and objective space. The proposed method is especially advantageous in computationally expensive cases, since the parametric representation of the Pareto set can be used as an inexpensive surrogate for the original problem during the decision making process. peerReviewed

A survey on handling computationally expensive multiobjective optimization problems using surrogates: non-nature inspired methods

2015

Computationally expensive multiobjective optimization problems arise, e.g. in many engineering applications, where several conflicting objectives are to be optimized simultaneously while satisfying constraints. In many cases, the lack of explicit mathematical formulas of the objectives and constraints may necessitate conducting computationally expensive and time-consuming experiments and/or simulations. As another challenge, these problems may have either convex or nonconvex or even disconnected Pareto frontier consisting of Pareto optimal solutions. Because of the existence of many such solutions, typically, a decision maker is required to select the most preferred one. In order to deal wi…

A NEW PROGRESSIVE DESIGN METHODOLOGY FOR COMPLEX SHEET METAL STAMPING OPERATIONS: COUPLING SPATIALLY DIFFERENTIATED RESTRAINING FORCES APPROACH AND M…

2010

The growing interest in sheet metal stamping processes, particularly in the automotive industry has led to three main issues in this field:*request of very complex shapes; *growing interest in springback control; *solution of multi-objective problems. These issues make a sheet metal stamping processes design very difficult and proper design methodologies to reduce times and costs are highly required. In this paper, a computer aided approach aiming to satisfy the mentioned issues is proposed. In particular, a progressive design approach based on the integration between numerical simulations, Response Surface Methodology (RSM) and Pareto optimal solutions search techniques was applied in orde…

Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach

2021

This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtained with the novel approach to those obtained with previously used approaches. We show that the novel approach guarantees the feasibility and robust efficiency of the produced solutions under all selected scenarios, while decreasing computation cost, addresses the scenario-dependency issues, and enables the decision-makers to explore the trade-off …

Biased Modern Heuristics for the OCST Problem

2011

Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.

2021

One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the non-dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the streng…