Search results for "Interactive methods"
showing 10 items of 34 documents
Interaktīvo metožu efektiviāte, mācot angļu valodas gramatiku vidusskolā
2016
Bakalaura darba mērķis ir pierādīt interaktīvo metožu efektivitāti, mācot saliktās tagadnes laiku angļu valodā. Šis pētījums sastāv četrām nodaļām. Pirmajā nodaļā akcentēts angļu valodas gramatikas nozīmīgums un sniegts ieskats gramatikas teorijā. Tiek aprakstītas galvenās iezīmes un atšķirības mutvārdu un rakstveida gramatikā, kā arī minēts, kāpēc angļu valodas gramatika būtu jāmāca un aprakstīta skolotāja loma mācību procesā. Otrajā nodaļā pētītas dažādas angļu valodas gramatikas mācīšanas tehnikas un metodes. Trešajā nodaļā aprakstīti interaktīvie paņēmieni, mācot angļu valodas gramatiku vidusskolā. Bakalaura darba praktiskā daļa ietver eksperimentu. Šī daļa veltīta novadīto stundu aprak…
A new preference handling technique for interactive multiobjective optimization without trading-off
2015
Because the purpose of multiobjective optimization methods is to optimize conflicting objectives simultaneously, they mainly focus on Pareto optimal solutions, where improvement with respect to some objective is only possible by allowing some other objective(s) to impair. Bringing this idea into practice requires the decision maker to think in terms of trading-off, which may limit the ability of effective problem solving. We outline some drawbacks of this and exploit another idea emphasizing the possibility of simultaneous improvement of all objectives. Based on this idea, we propose a technique for handling decision maker’s preferences, which eliminates the necessity to think in terms of t…
An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems
2015
This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…
An interactive surrogate-based method for computationally expensive multiobjective optimisation
2019
Many disciplines involve computationally expensive multiobjective optimisation problems. Surrogate-based methods are commonly used in the literature to alleviate the computational cost. In this paper, we develop an interactive surrogate-based method called SURROGATE-ASF to solve computationally expensive multiobjective optimisation problems. This method employs preference information of a decision-maker. Numerical results demonstrate that SURROGATE-ASF efficiently provides preferred solutions for a decision-maker. It can handle different types of problems involving for example multimodal objective functions and nonconvex and/or disconnected Pareto frontiers. peerReviewed
Why Use Interactive Multi-Objective Optimization in Chemical Process Design?
2008
Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements on the optimization methods used. In this chapter, we point out some shortcomings of some widely used basic methods of multi-objective optimization. As an alternative, we suggest using interactive approaches where the role of a decision maker or a designer is emphasized. Interactive multi-objective optimization has been shown to suit well for chemical process design problems because it takes the preferences of the decision maker into account in an iterative manner tha…
NAUTILUS framework : towards trade-off-free interaction in multiobjective optimization
2016
In this paper, we present a framework of different interactive NAUTILUS methods for multiobjective optimization. In interactive methods, the decision maker iteratively sees solution alternatives and provides one’s preferences in order to find the most preferred solution. We question the widely used setting that the solutions shown to the decision maker should all be Pareto optimal which implies that improvement in any objective function necessitates allowing impairment in some others. Instead, in NAUTILUS we enable the decision maker to make a free search without having to trade-off by starting from an inferior solution and iteratively approaching the Pareto optimal set by allowing all obje…
Data-driven Interactive Multiobjective Optimization : Challenges and a Generic Multi-agent Architecture
2020
In many decision making problems, a decision maker needs computer support in finding a good compromise between multiple conflicting objectives that need to be optimized simultaneously. Interactive multiobjective optimization methods have a lot of potential for solving such problems. However, the growth of complexity in problem formulations and the abundance of data bring new challenges to be addressed by decision makers and method developers. On the other hand, advances in the field of artificial intelligence provide opportunities in this respect. We identify challenges and propose directions of addressing them in interactive multiobjective optimization methods with the help of multiple int…
Interactive multiobjective optimization with NIMBUS for decision making under uncertainty
2013
We propose an interactive method for decision making under uncertainty, where uncertainty is related to the lack of understanding about consequences of actions. Such situations are typical, for example, in design problems, where a decision maker has to make a decision about a design at a certain moment of time even though the actual consequences of this decision can be possibly seen only many years later. To overcome the difficulty of predicting future events when no probabilities of events are available, our method utilizes groupings of objectives or scenarios to capture different types of future events. Each scenario is modeled as a multiobjective optimization problem to represent differe…
Implementation aspects of interactive multiobjective optimization for modeling environments: The case of GAMS-NIMBUS
2014
Abstract. Interactive multiobjective optimization methods have provided promising results in the literature but still their implementations are rare. Here we introduce a core structure of interactive methods to enable their convenient implementation. We also demonstrate how this core structure can be applied when implementing an interactive method using a modeling environment. Many modeling environments contain tools for single objective optimization but not for interactive multiobjective optimization. Furthermore, as a concrete example, we present GAMS-NIMBUS Tool which is an implementation of the classification-based NIMBUS method for the GAMS modeling environment. So far, interactive met…
Solving multiobjective optimization problems with decision uncertainty: an interactive approach
2018
We propose an interactive approach to support a decision maker to find a most preferred robust solution to multiobjective optimization problems with decision uncertainty. A new robustness measure that is understandable for the decision maker is incorporated as an additional objective in the problem formulation. The proposed interactive approach utilizes elements of the synchronous NIMBUS method and is aimed at supporting the decision maker to consider the objective function values and the robustness of a solution simultaneously. In the interactive approach, we offer different alternatives for the decision maker to express her/his preferences related to the robustness of a solution. To conso…