Search results for "multi-objective"
showing 10 items of 220 documents
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
2019
In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed
A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem
2017
A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. peerReviewed
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…
Multi-modal search for multiobjective optimization: an application to optimal smart grids management
2012
This paper studies the possibility to use efficient multimodal optimizers for multi-objective optimization. In this paper, the application area considered for such new approach is the optimal dispatch of energy sources in smart microgrids. The problem indeed shows a non uniform Pareto front and requires efficient optimal search methods. The idea is to exploit the potential of agents in population-based heuristics to improve diversity in the Pareto front, where solutions show the same rank and are thus equally weighted. Since Pareto dominance is at the basis of the theory of multi-objective optimization, most algorithms show the non dominance ranking as quality indicator, with some problem i…
Future wood demands and ecosystem services trade-offs: A policy analysis in Norway
2023
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving m…
Multi-objective human resources allocation in R&D projects planning
2009
In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses on three fundamental aspects of human resources: the different skill levels, the learning process and the social relationships existing in working teams. The resolution approach for the multi-objective problem consists of two steps: firstly, a set of non-dominated solutions is obtained by exploring the…
A Matrix Model For An Energy Management System Based On Multi-Carrier Energy Hub Approach
2015
The INGRID FP7 European co-funded project studies several methodologies concerning hydrogen production and storage, aiming to provide services to electricity system operators for suitably balancing electrical supply and demand. In such a context, the problem of integrating different carriers into a single multi-hub optimiser represents a challenging topic for the research. This paper depicts the Energy Management System (EMS) of the plant which will be developed and built as a prototype of the INGRID system. The approach followed for the EMS design and development takes the cue from the matrix model presented in the rest of the paper, as well as the general optimisation problem formulation …
Coupling dynamic simulation and interactive multiobjective optimization for complex problems: An APROS-NIMBUS case study
2014
Dynamic process simulators for plant-wide process simulation and multiobjective optimization tools can be used by industries as a means to cut costs and enhance profitability. Specifically, dynamic process simulators are useful in the process plant design phase, as they provide several benefits such as savings in time and costs. On the other hand, multiobjective optimization tools are useful in obtaining the best possible process designs when multiple conflicting objectives are to be optimized simultaneously. Here we concentrate on interactive multiobjective optimization. When multiobjective optimization methods are used in process design, they need an access to dynamic process simulators, …
Hybrid evolutionary multi-objective optimization with enhanced convergence and diversity
2011
Optimal design of k-out-of-n systems
2016
The present paper is aimed at finding the best compromise to design a system k-out-of-n reliability configuration by means of the formulation of a multi-objective mathematical model. The Pareto front, which is the set of non-dominated solutions, is determined by considering the stationary availability and the achievable profit as objectives to be simultaneously optimized. The Pareto front represents a useful tool for the analyst to make the choice related to the analyzed design problem. In addition, the knowledge of the Pareto front permits to consider different design scenarios.