Search results for "Pareto"
showing 10 items of 126 documents
Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors
2017
Abstract Recent years have seen a growing trend in wind and solar energy generation globally and it is expected that an important percentage of total energy production comes from these energy sources. However, they present inherent variability that implies fluctuations in energy generation that are difficult to forecast. Thus, forecasting errors have a considerable role in the impacts and costs of renewable energy integration, management, and commercialization. This study presents an important advance in the task of analyzing prediction models, in particular, in the timing component of prediction error, which improves previous pioneering results. A new method to match time series is defined…
Changes in Transport and Non Transport Costs: Local vs. Global Impacts in a Spatial Network
2007
We develop a multi-country Dixit-Stiglitz trade model and analyze how industry location and welfare respond to changes in: (i) transport frictions (e.g., infrastructure, transportation technology); and (ii) non-transport frictions (e.g., tariffs, standards and regulations). We show that changes in non-transport frictions, which are usually origin-destination specific, do not allow for any clear prediction as to changes in industry location and welfare; whereas changes in transport frictions, which are usually not origin-destination specific, may allow for such predictions. In particular, we show that reductions in transport frictions occurring at links around which the spatial network is lo…
Prices and Pareto optima
2006
We provide necessary conditions for Pareto optimum in economies where tastes or technologies may be nonconvex, nonsmooth, and affected by externalities. Firms can pursue own objectives, much like the consumers. Infinite-dimensional commodity spaces are accommodated. Public goods and material balances are accounted for as special instances of linear restrictions.
A Generalized Framework for Optimal Sizing of Distributed Energy Resources in Micro-Grids Using an Indicator-Based Swarm Approach
2014
In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated usin…
A double-shell design approach for multiobjective optimal design of microgrids
2010
This work develops a new double shell approach to optimal design for multi-objective optimally managed systems. The cost of each design solution can be defined by the evaluation of operational issues and capital costs. In most systems, the correct definition of operational issues can be deduced by means of the solution of a multi-objective optimization problem. The evaluation of each design solution must thus be deduced using the outcome of a multi-objective optimization run, namely a Pareto hyper-surface in the n-dimensional space of operational objectives. In the literature, the design problem is usually solved by considering a single objective formulation of the operational issue. In thi…
Comparison between Entropy and Resilience as Indirect Measures of Reliability in the Framework of Water Distribution Network Design
2014
Abstract The aim of this paper is to investigate which between the entropy and resilience indices represents a better indirect measure of reliability in the framework of water distribution network design. The methodology adopted consisted of (a) multi-objective optimizations performed in order to minimize costs and maximize reliability, expressed by means of one of the indirect indices at time; (b) retrospective performance assessment of the solutions of Pareto fronts obtained. Two case studies of different topological complexity were considered. Results showed that indices based on energetic concepts (resilience and modified resilience) represent a better compact estimate of reliability th…
Water quality sensor placement: a multi-objective and multi-criteria approach
2021
[EN] To satisfy their main goal, namely providing quality water to consumers, water distribution networks (WDNs) need to be suitably monitored. Only well designed and reliable monitoring data enables WDN managers to make sound decisions on their systems. In this belief, water utilities worldwide have invested in monitoring and data acquisition systems. However, good monitoring needs optimal sensor placement and presents a multi-objective problem where cost and quality are conflicting objectives (among others). In this paper, we address the solution to this multi-objective problem by integrating quality simulations using EPANET-MSX, with two optimization techniques. First, multi-objective op…
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…
Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems
2023
Abstract For offline data-driven multiobjective optimization problems (MOPs), no new data is available during the optimization process. Approximation models (or surrogates) are first built using the provided offline data and an optimizer, e.g. a multiobjective evolutionary algorithm, can then be utilized to find Pareto optimal solutions to the problem with surrogates as objective functions. In contrast to online data-driven MOPs, these surrogates cannot be updated with new data and, hence, the approximation accuracy cannot be improved by considering new data during the optimization process. Gaussian process regression (GPR) models are widely used as surrogates because of their ability to pr…
Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process
2019
The design of water treatment plants requires simultaneous analysis of technical, economic and environmental aspects, identified by multiple conflicting objectives. We demonstrated the advantages of an interactive multiobjective optimization (MOO) method over a posteriori methods in an unexplored field, namely the design of a biological treatment plant for drinking water production, that tackles the process drawbacks, contrarily to what happens in a traditional volumetric-load-driven design procedure. Specifically, we consider a groundwater denitrification biofilter, simulated by the Activated Sludge Model modified with two-stage denitrification kinetics. Three objectives were defined (nitr…