Search results for "monitavoiteoptimointi"
showing 10 items of 81 documents
Task-based visual analytics for interactive multiobjective optimization
2020
We study how visual interaction techniques considered in visual analytics can be utilized when implementing interactive multiobjective optimization methods, where a decision maker iteratively participates in the solution process. We want to benefit from previous research and avoid re-inventing ideas. Our aim is to widen awareness and increase the applicability of interactive methods for solving real-world problems. As a concrete approach, we introduce seven high-level tasks that are relevant for interactive methods. These high-level tasks are based on low-level tasks proposed in the visual analytics literature. In addition, we give an example on how the high-level tasks can be implemented a…
Visualizations for Decision Support in Scenario-based Multiobjective Optimization
2021
Reproducibility artifacts for: Babooshka Shavazipour, Manuel López-Ibáñez, and Kaisa Miettinen. Visualizations for Decision Support in Scenario-based Multiobjective Optimization. Information Sciences, 2021. doi:10.1016/j.ins.2021.07.025. Abstract: We address challenges of decision problems when managers need to optimize several conflicting objectives simultaneously under uncertainty. We propose visualization tools to support the solution of such scenario-based multiobjective optimization problems. Suitable graphical visualizations are necessary to support managers in understanding, evaluating, and comparing the performances of management decisions according to all objec…
Optimal sample allocation conditioned on a small area model, estimator, and auxiliary data
2018
We have studied optimal sample allocation, associated with small area estimation, when the objective is to obtain as accurate estimates as possible, for the population and for the subpopulations, called as areas here. It is a question of a two-level optimization problem. The basic premise is composed of planned areas, stratified sampling, and small overall sample size predetermined by restricted time and budget resources. Low sample sizes are common in market surveys. During this thesis, we have developed new allocation methods, based on a small area model, estimator, and auxiliary data. The final method, the three-term Pareto allocation, is based on the three terms of the mean-squared erro…
An Artificial Decision Maker for Comparing Reference Point Based Interactive Evolutionary Multiobjective Optimization Methods
2021
Comparing interactive evolutionary multiobjective optimization methods is controversial. The main difficulties come from features inherent to interactive solution processes involving real decision makers. The human can be replaced by an artificial decision maker (ADM) to evaluate methods quantitatively. We propose a new ADM to compare reference point based interactive evolutionary methods, where reference points are generated in different ways for the different phases of the solution process. In the learning phase, the ADM explores different parts of the objective space to gain insight about the problem and to identify a region of interest, which is studied more closely in the decision phas…
Connections Between Single-Level and Bilevel Multiobjective Optimization
2011
The relationship between bilevel optimization and multiobjective optimization has been studied by several authors and there have been repeated attempts to establish a link between the two. We unify the results from the literature and generalize them for bilevel multiobjective optimization. We formulate sufficient conditions for an arbitrary binary relation to guarantee equality between the efficient set produced by the relation and the set of optimal solutions to a bilevel problem. In addition, we present specially structured bilevel multiobjective optimization problems motivated by real-life applications and an accompanying binary relation permitting their reduction to single-level multiob…
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
Surrogate assisted interactive multiobjective optimization in energy system design of buildings
2022
In this paper, we develop a novel evolutionary interactive method called interactive K-RVEA, which is suitable for computationally expensive problems. We use surrogate models to replace the original expensive objective functions to reduce the computation time. Typically, in interactive methods, a decision maker provides some preferences iteratively and the optimization algorithm narrows the search according to those preferences. However, working with surrogate model swill introduce some inaccuracy to the preferences, and therefore, it would be desirable that the decision maker can work with the solutions that are evaluated with the original objective functions. Therefore, we propose a novel…
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 evolutionary multiobjective optimization with modular physical user interface
2022
© 2022 Copyright held by the owner/author(s). Incorporating the preferences of a domain expert, a decision-maker (DM), in solving multiobjective optimization problems increased in popularity in recent years. The DM can choose to use different types of preferences depending on his/her comfort, requirements, or the problem being solved. Most papers, where preference-based and interactive algorithms have been proposed, do not pay attention to the user interfaces and input devices. If they do, they use character or graphics-based preference input methods. We propose the option of using a physical or tactile input device that gives the DM a better sense of control over providing his/her preferen…
On approaches for solving computationally expensive multiobjective optimization problems
2016
In this thesis, we consider solving computationally expensive multiobjective optimization problems that take into account the preferences of a decision maker (DM). The aim is to support the DM in identifying the most preferred solution for problems that have several conflicting objectives and when the evaluation of the candidate solutions is time consuming. This is conducted by replacing computationally expensive functions with computationally inexpensive functions, known as surrogates. First, based on a literature survey, we introduce two frameworks, i.e., a sequential and an adaptive framework, based on which surrogate-based methods are classified and compared. We then identify relevant cha…