Search results for "making"

Sekcijas "Globalizācijas ietekme uz valsts ekonomiku un biznesu" Ekonomikas un vadības fakultātē (28. janvāris, 2016): Referātu tēzes

2016

Employee Sensemaking on the Importance of Sustainability Reporting in Sustainability Identity Change

2017

This study examines employee sensemaking processes in order to understand the role of sustainability reporting in organizational identity change. Through an analysis of 52 interviews with employees in two Finnish companies, we develop sensemaking frames for understanding the role of sustainability reporting in organizational identity change. The three sensemaking frames are individualistic, relational and decoupled. Each of these sensemaking frames differs in stakeholder orientation. They indicate that sensemaking influences the interpretation of how important sustainability reporting is for organizational identity change towards sustainability. The study shows how the individualistic and r…

On the role of the upper part of words in lexical access: evidence with masked priming.

2012

More than 100 years ago, Huey (1908) indicated that the upper part of words was more relevant for perception than the lower part. Here we examined whether mutilated words, in their upper/lower portions (e.g., , , , ), can automatically access their word units in the mental lexicon. To that end, we conducted four masked repetition priming experiments with the lexical decision task. Results showed that mutilated primes produced a sizeable masked repetition priming effect. Furthermore, the magnitude of the masked repetition priming effect was greater when the upper part of the primes was preserved than when the lower portion was preserved –this was the case not only when the mutilated words we…

Manipulating the alpha level cannot cure significance testing

2018

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple in…

ANOVA-MOP: ANOVA Decomposition for Multiobjective Optimization

2018

Real-world optimization problems may involve a number of computationally expensive functions with a large number of input variables. Metamodel-based optimization methods can reduce the computational costs of evaluating expensive functions, but this does not reduce the dimension of the search domain nor mitigate the curse of dimensionality effects. The dimension of the search domain can be reduced by functional anova decomposition involving Sobol' sensitivity indices. This approach allows one to rank decision variables according to their impact on the objective function values. On the basis of the sparsity of effects principle, typically only a small number of decision variables significantl…

A solution process for simulation-based multiobjective design optimization with an application in the paper industry

2014

In this paper, we address some computational challenges arising in complex simulation-based design optimization problems. High computational cost, black-box formulation and stochasticity are some of the challenges related to optimization of design problems involving the simulation of complex mathematical models. Solving becomes even more challenging in case of multiple conflicting objectives that must be optimized simultaneously. In such cases, application of multiobjective optimization methods is necessary in order to gain an understanding of which design offers the best possible trade-off. We apply a three-stage solution process to meet the challenges mentioned above. As our case study, w…

Interactive Nonlinear Multiobjective Optimization Methods

2016

An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory Pareto optimal solution can be found for her or his. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated. As the role of the decision maker is very important in interactive methods, methods presented are classified according to the type of preference information that the decision maker is assumed to provide. peerReviewed

PAINT : Pareto front interpolation for nonlinear multiobjective optimization

2011

A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g., for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive meth…

Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm

2019

We formulate and solve a real-world shape design optimization problem of an air intake ventilation system in a tractor cabin by using a preference-based surrogate-assisted evolutionary multiobjective optimization algorithm. We are motivated by practical applicability and focus on two main challenges faced by practitioners in industry: 1) meaningful formulation of the optimization problem reflecting the needs of a decision maker and 2) finding a desirable solution based on a decision maker’s preferences when solving a problem with computationally expensive function evaluations. For the first challenge, we describe the procedure of modelling a component in the air intake ventilation system wi…

Handling expensive multiobjective optimization problems with evolutionary algorithms

2017

Multiobjective optimization problems (MOPs) with a large number of conflicting objectives are often encountered in industry. Moreover, these problem typically involve expensive evaluations (e.g. time consuming simulations or costly experiments), which pose an extra challenge in solving them. In this thesis, we first present a survey of different methods proposed in the literature to handle MOPs with expensive evaluations. We observed that most of the existing methods cannot be easily applied to problems with more than three objectives. Therefore, we propose a Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) for problems with at least three expensive objectives. The alg…