Composite structures offer unique mechanical and physical properties enabled by material heterogeneity. To harness these in stress-constrained topology optimization, the incorporation of multiple materials is necessary. Established studies field typically assume same yield criterion for all candidate while vary their stiffness strengths. open up full design capability composite structures, we p...

We argue for the usefulness of convenient optimization criteria, when building scalable and efficient instance retrieval inference services for ontology-based applications. We discuss several optimization criteria, especially a dedicated load balancing strategy, evaluate the approach with practical experiments on a particular implementation and present results.

The topic of this paper are discrete decision problems with multiple criteria. We rst deene discrete multiple criteria decision problems and introduce a classiication scheme for multiple criteria optimization problems. To do so we use multiple criteria optimization classes. The main result is a characterization of the class of lexicographic max-ordering problems by two very useful properties, r...

In this article, model selection for support vector machines is viewed as a multi-objective optimization problem, where model complexity and training accuracy define two conflicting objectives. Different optimization criteria are evaluated: Split modified radius margin bounds, which allow for comparing existing model selection criteria, and the training error in conjunction with the number of s...

Usually the primary goal for the application of optimization algorithms is convergence to the global optimum, and the secondary goal is to use the least computational effort. By application of different stopping criteria the achievement of both objectives is influenced: If an optimization run is terminated too early, convergence may not be reached, but on the other hand computational resources ...

Practical optimization problems such as job-shop scheduling often involve optimization criteria that change over time. Repair-based frameworks have been identi ed as exible computational paradigms for difcult combinatorial optimization problems. Since the control problem of repair-based optimization is severe, Reinforcement Learning (RL) techniques can be potentially helpful. However, some of t...

Real life problems involve seldom only one criterion, but multiple criteria should be optimised at the same time. The criteria can even be conflicting each other, so the classical techniques used in single criteria optimization cannot be simply reused. Many ideas have been presented in the literature for addressing multiple criteria optimization problems; one of the ideas is to provide the so-c...

The present paper addresses the issue of optimization of reliability acceptance criteria for components of complex engineered systems with given criterion to acceptable system risk. To this end, the paper first describes how complex engineered systems may be modelled hierarchically by use of Bayesian probabilistic networks. The Bayesian probabilistic network serves as a function relating the re...