Search results for "multi-objective"
showing 10 items of 220 documents
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…
Multi-sensor Fusion through Adaptive Bayesian Networks
2011
Common sensory devices for measuring environmental data are typically heterogeneous, and present strict energy constraints; moreover, they are likely affected by noise, and their behavior may vary across time. Bayesian Networks constitute a suitable tool for pre-processing such data before performing more refined artificial reasoning; the approach proposed here aims at obtaining the best trade-off between performance and cost, by adapting the operating mode of the underlying sensory devices. Moreover, self-configuration of the nodes providing the evidence to the Bayesian network is carried out by means of an on-line multi-objective optimization.
More is more? : Forest management allocation at different spatial scales to mitigate conflicts between ecosystem services
2017
Context: Multi-objective management can mitigate conflicts among land-use objectives. However, the effectiveness of a multi-objective solution depends on the spatial scale at which land-use is optimized. This is because the ecological variation within the planning region influences the potential for site-specific prioritization according to the different objectives. Objectives: We optimized the allocation of forest management strategies to maximize the joint production of two conflicting objectives, timber production and carbon storage, at increasing spatial scales. We examined the impacts of the extent of the planning region on the severity of the conflict, the potential for its mitigation…
Sets of Efficiency in a Normed Space and Inner Product
1987
In a normed space X the distances to the points of a given set A being considered as the objective functions of a multicriteria optimization problem, we define four sets of efficiency (efficient, strictly efficient, weakly efficient and properly efficient points). Instead of studying properties of the sets of efficiency according to properties of the norm, we investigate an inverse problem: deduce properties of the norm of X from properties of the sets of efficiency, valid for every finite subset A of X.
NIMBUS — Interactive Method for Nondifferentiable Multiobjective Optimization Problems
1996
An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. We assume that every objective function is to be minimized The idea of NIMBUS is that the decision maker can easily indicate what kind of improvements are desired and what kind of impairments are tolerable at the point considered.
A Visualizable Test Problem Generator for Many-Objective Optimization
2022
Visualizing the search behavior of a series of points or populations in their native domain is critical in understanding biases and attractors in an optimization process. Distancebased many-objective optimization test problems have been developed to facilitate visualization of search behavior in a two-dimensional design space with arbitrarily many objective functions. Previous works have proposed a few commonly seen problem characteristics into this problem framework, such as the definition of disconnected Pareto sets and dominance resistant regions of the design space. The authors’ previous work has advanced this research further by providing a problem generator to automatically create use…
Introduction to General Duality Theory for Multi-Objective Optimization
1992
This is intended as a comprehensive introduction to the duality theory for vector optimization recently developed by C. Malivert and the present author [3]. It refers to arbitrarily given classes of mappings (dual elements) and extends the general duality theory proposed for scalar optimization by E. Balder, S. Kurcyusz and the present author [1] and P. Lindberg.
Trade-offs among intensive forestry, ecosystem services and biodiversity in boreal forests
2018
Finnish forests are used extensively for timber production but are also providers of other ecosystem services and harbor unique biodiversity. The ecosystem services approach has so far been used marginally in the context of Finnish forestry; however, due to the multiple values associated with Finnish forests and the impacts forestry operations have on forest ecosystems, it is clearly applicable in this context. In this thesis, I studied the occurrence and severity of trade-offs among ecosystem services and biodiversity conservation in Finnish forests. I used forest inventory data, forest growth simulations, and multi-objective optimization to reveal how the severity of the trade-offs varies…
Interactive Method NIMBUS for Nondifferentiable Multiobjective Optimization Problems
1997
An interactive method, NIMBUS, for nondifferentiable multiobjective optimization problems is introduced. The method is capable of handling several nonconvex locally Lipschitzian objective functions subject to nonlinear (possibly nondifferentiable) constraints. The idea of NIMBUS is that the decision maker can easily indicate what kind of improvements are desired and what kind of impairments are tolerable at the point considered. The decision maker is asked to classify the objective functions into five different classes: those to be improved, those to be improved down to some aspiration level, those to be accepted as they are, those to be impaired till some upper bound, and those allowed to …
A Feature Rich Distance-Based Many-Objective Visualisable Test Problem Generator
2019
In optimiser analysis and design it is informative to visualise how a search point/population moves through the design space over time. Visualisable distance-based many-objective optimisation problems have been developed whose design space is in two-dimensions with arbitrarily many objective dimensions. Previous work has shown how disconnected Pareto sets may be formed, how problems can be projected to and from arbitrarily many design dimensions, and how dominance resistant regions of design space may be defined. Most recently, a test suite has been proposed using distances to lines rather than points. However, active use of visualisable problems has been limited. This may be because the ty…