Search results for " optimization"
showing 10 items of 2367 documents
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…
A decomposition approach for multidimensional knapsacks with family-split penalties
2022
The optimization of Multidimensional Knapsacks with Family-Split Penalties has been introduced in the literature as a variant of the more classical Multidimensional Knapsack and Multi-Knapsack problems. This problem deals with a set of items partitioned in families, and when a single item is picked to maximize the utility, then all items in its family must be picked. Items from the same family can be assigned to different knapsacks, and in this situation split penalties are paid. This problem arises in real applications in various fields. This paper proposes a new exact and fast algorithm based on a specific Combinatorial Benders Cuts scheme. An extensive experimental campaign computational…
On approaches for solving computationally expensive multiobjective optimization problems
2016
In this thesis, we consider solving computationally expensive multiobjective optimization problems that take into account the preferences of a decision maker (DM). The aim is to support the DM in identifying the most preferred solution for problems that have several conflicting objectives and when the evaluation of the candidate solutions is time consuming. This is conducted by replacing computationally expensive functions with computationally inexpensive functions, known as surrogates. First, based on a literature survey, we introduce two frameworks, i.e., a sequential and an adaptive framework, based on which surrogate-based methods are classified and compared. We then identify relevant cha…
Robust delay-dependent H∞ control of uncertain time-delay systems with mixed neutral, discrete, and distributed time-delays and Markovian switching p…
2011
Author's version of an article published in the journal: IEEE Transactions on Circuits and Systems I: Regular Papers. Also available from the publisher at: http://dx.doi.org/10.1109/tcsi.2011.2106090 The problem of robust mode-dependent delayed state feedback H ∞ control is investigated for a class of uncertain time-delay systems with Markovian switching parameters and mixed discrete, neutral, and distributed delays. Based on the LyapunovKrasovskii functional theory, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities for the stochastic stability and stabilization of the considered system using some free matrices. The desired control is …
Wireless Sensor Network Operating System Design Rules Based on Real-World Deployment Survey
2013
Wireless sensor networks (WSNs) have been a widely researched field since the beginning of the 21st century. The field is already maturing, and TinyOS has established itself as the de facto standard WSN Operating System (OS). However, the WSN researcher community is still active in building more flexible, efficient and user-friendly WSN operating systems. Often, WSN OS design is based either on practical requirements of a particular research project or research group's needs or on theoretical assumptions spread in the WSN community. The goal of this paper is to propose WSN OS design rules that are based on a thorough survey of 40 WSN deployments. The survey unveils trends of WSN applic…
Lipschitz Carnot-Carathéodory Structures and their Limits
2022
AbstractIn this paper we discuss the convergence of distances associated to converging structures of Lipschitz vector fields and continuously varying norms on a smooth manifold. We prove that, under a mild controllability assumption on the limit vector-fields structure, the distances associated to equi-Lipschitz vector-fields structures that converge uniformly on compact subsets, and to norms that converge uniformly on compact subsets, converge locally uniformly to the limit Carnot-Carathéodory distance. In the case in which the limit distance is boundedly compact, we show that the convergence of the distances is uniform on compact sets. We show an example in which the limit distance is not…
Distributed optimal power flow for islanded microgrids: An application to the Smart Polygeneration Microgrid of the Genoa University
2016
In this work, the application of an original distributed optimal power flow method to test a microgrid in the Savona area, Italy is proposed. The microgrid shows different types of Distributed Energy Resources (DERs) and is connected to the main grid through a fixed power bus. Due to the high computational speed, the applied distributed Optimal Power Flow can be performed almost in real time, i.e. every 5 minutes or less. The operating solution found for generators, simply using local information, corresponds to a suboptimal condition with reduced losses, bus voltages and line currents within constrained intervals. The distributed optimization algorithm is iterative, but also fast. It is ba…
Arc routing problems with drones
2023
La tecnología emergente de vehículos aéreos no tripulados, comúnmente conocidos como drones, ha brindado nuevas oportunidades para los profesionales de la logística urbana en la última década. El transporte ha jugado siempre un papel crucial en la sociedad y en la economía, y un motor fundamental del desarrollo económico en los últimos tiempos ha sido la inversión en sistemas de transporte cada vez más eficientes. Los drones presentan ventajas atractivas en comparación con los vehículos terrestres estándar, como evitar la congestión en las redes viales, eliminar el riesgo del personal en operaciones de difícil acceso u obtener una mayor precisión de medición en la inspección de infraestruct…
Real-Time Minimization Power Losses by Driven Primary Regulation in Islanded Microgrids
2020
Islanded microgrids are small networks that work independently from the main grid. The frequency and voltage in islanded microgrids are affected directly by the output power of distributed generators and power demand variations. In this work, a real-time driven primary regulation, which relies on optimized P-f droop coefficients, is proposed. In all operating conditions, it minimizes the power losses for islanded microgrids. The proposed configuration will allow the optimization modules to interact with each other and adjust parameters producing a suitable power sharing among generators. The methodology is tested based on a hardware-in-the-loop experimental set-up where distributed generato…