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Papers by Giampaolo Liuzzi

Research paper thumbnail of Improving P300 Speller performance by means of optimization and machine learning

Annals of Operations Research

Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment byp... more Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are ...

Research paper thumbnail of Hybridization of Multi-Objective Deterministic Particle Swarm with Derivative-Free Local Searches

Mathematics

The paper presents a multi-objective derivative-free and deterministic global/local hybrid algori... more The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based o...

Research paper thumbnail of A multi-objective DIRECT algorithm for ship hull optimization

Computational Optimization and Applications

The paper is concerned with black-box nonlinear constrained multi-objective optimization problems... more The paper is concerned with black-box nonlinear constrained multi-objective optimization problems. Our interest is the definition of a multi-objective deterministic partition-based algorithm. The main target of the proposed algorithm is the solution of a real ship hull optimization problem. To this purpose and in pursuit of an efficient method, we develop an hybrid algorithm by coupling a multi-objective DIRECT-type algorithm with an efficient derivative-free local algorithm. The results obtained on a set of "hard" nonlinear constrained multi-objective test problems show viability of the proposed approach. Results on a hull-form optimization of a high-speed catamaran (sailing in head waves in the North Pacific Ocean) are also presented. In order to consider a real ocean environment, stochastic sea state and speed are taken into account. The problem is formulated as a multi-objective optimization aimed at (i) the reduction of the expected value of the mean total resistance in irregular head waves, at variable speed and (ii) the increase of the ship operability, with respect to a set of motion-related constraints. We show that the hybrid method performs well also on this industrial problem.

Research paper thumbnail of An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints

Computational Optimization and Applications

Research paper thumbnail of Parallelized hybrid optimization methods for nonsmooth problems using NOMAD and linesearch

Computational and Applied Mathematics

Research paper thumbnail of A decomposition algorithm for unconstrained optimization problems with partial derivative information

Research Report Series of Iasi Cnr Rome Italy, 2009

In this paper we consider the problem of minimizing a nonlinear function using partial derivative... more In this paper we consider the problem of minimizing a nonlinear function using partial derivative knowledge. Namely, the objective function is such that its derivatives with respect to a pre-specified block of variables cannot be computed. To solve the problem we propose a block decomposition method that takes advantage of both derivative-free and derivative-based iterations to account for the features of the objective function. Under standard assumptions, we manage to prove global convergence of the method to stationary points of the problem.

Research paper thumbnail of A derivative-free algorithm for inequality constrained nonlinear programming

Research Report Series of Iasi Cnr Rome Italy, 2007

Research paper thumbnail of A first-order method for <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>e</mi><mi>l</mi><msub><mi>l</mi><mn>0</mn></msub></mrow><annotation encoding="application/x-tex">ell_0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8444em;vertical-align:-0.15em;"></span><span class="mord mathnormal">e</span><span class="mord mathnormal" style="margin-right:0.01968em;">l</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.01968em;">l</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3011em;"><span style="top:-2.55em;margin-left:-0.0197em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">0</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span>-penalized problems with simple constraints

Research Report Series of Iasi Cnr Rome Italy, 2012

Research paper thumbnail of Ship hydrodynamic optimization by local hybridization of deterministic derivative-free global algorithms

Applied Ocean Research, 2016

Simulation-based design optimization methods integrate computer simulations, design modification ... more Simulation-based design optimization methods integrate computer simulations, design modification tools, and optimization algorithms. In hydrodynamic applications, often objective functions are computationally expensive and noisy, their derivatives are not directly provided, and the existence of local minima cannot be excluded a priori, which motivates the use of deterministic derivative-free global optimization algorithms. The enhancement of two algorithms of this type, DIRECT (DIviding RECTangles) and DPSO (Deterministic Particle Swarm Optimization), is presented based on global/local hybridization with derivative-free line search methods. The hull-form optimization of the DTMB 5415 model is solved for the reduction of the calm-water resistance at Fr = 0.25, using potential flow and RANS solvers. Six and eleven design variables are used respectively, modifying both the hull and the sonar dome. Hybrid algorithms show a faster convergence towards the global minimum than the original global methods and are a viable option for ship hydrodynamic optimization. A significant resistance reduction is achieved both by potential flow and RANS-based optimizations, showing the effectiveness of the optimization procedure.

Research paper thumbnail of Derivative-free global ship design optimization using global/local hybridization of the DIRECT algorithm

Optimization and Engineering, 2015

A simulation-based derivative-free global optimization of the hullform of a military vessel is pr... more A simulation-based derivative-free global optimization of the hullform of a military vessel is presented, aimed at the reduction of the resistance in calm water. The objective function is of the black-box type, computationally expensive and characterized by noise and non-smoothness. The presence of local minima cannot be excluded a priori. For these reasons, the use of derivative-free, global, DIRECT-type algorithms is proposed. Specifically, a recent hybridization of the DIRECT algorithm by local minimization is applied, and compared with a novel strategy for the management of the local searches. Comparative results are reported on a set of well-known and well-established test problems and on the simulation-based hull-form optimization problem.

Research paper thumbnail of A global optimization algorithm for protein structure alignment

Research Report Series of Iasi Cnr Rome Italy, 2008

Research paper thumbnail of Global Optimization of Simulation Based Complex Systems

Operations Research/Computer Science Interfaces Series, 2015

Research paper thumbnail of Combined cycle unit commitment in a changing electricity market scenario

International Journal of Electrical Power & Energy Systems, 2015

ABSTRACT For Generation Companies (GENCOs) one of the most relevant issue is the commitment of th... more ABSTRACT For Generation Companies (GENCOs) one of the most relevant issue is the commitment of the units, the scheduling of them over a daily (or longer) time frame, with the aim of obtaining the best profit. It strongly depends on the plant operational generation costs, which depend in turn on the choices taken at the design stage; it follows that design technical choices should also aim at determining the best generation cost structure of generating units with respect to the market opportunities. In the paper the unit commitment (UC) problem has been considered, with highlights on changes in the market scenario. The paper analyzes the relevance of some design choices (structure, size, regulation type) on the economics of the operation of gas–steam combined cycle generating units. To solve the UC problem, a recently proposed method for mixed integer nonlinear programming problems, with the use of a derivative free algorithm to solve the continuous subproblems, has been considered. The results for two GENCOs are reported: one managing a single unit and the other managing three units. Numerical examples show the sensitivity of the UC solutions to the market conditions and to the design choices on the regulation type in the evolving scenario of the Italian Electricity Market.

Research paper thumbnail of Diserafino Liuzzi Piccialli Riccio Toraldo

We present a modification of the DIRECT (DIviding RECTangles) algorithm, called DIRECT-G, to solv... more We present a modification of the DIRECT (DIviding RECTangles) algorithm, called DIRECT-G, to solve a box-constrained global optimization problem arising in the detection of gravitational waves emitted by coalescing binary systems

Research paper thumbnail of Appunti del corso di Analisi delle Decisioni

Research paper thumbnail of Nonmonotone GRASP

Research paper thumbnail of Nuovi metodi per l’ottimizzazione vincolata non lineare

Research paper thumbnail of New methods for nonlinear constrained optimization

Research paper thumbnail of Unit commitment by nonlinear mixed variable programming

Research paper thumbnail of Metodi di ottimizzazione vincolata

Research paper thumbnail of Improving P300 Speller performance by means of optimization and machine learning

Annals of Operations Research

Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment byp... more Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are ...

Research paper thumbnail of Hybridization of Multi-Objective Deterministic Particle Swarm with Derivative-Free Local Searches

Mathematics

The paper presents a multi-objective derivative-free and deterministic global/local hybrid algori... more The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based o...

Research paper thumbnail of A multi-objective DIRECT algorithm for ship hull optimization

Computational Optimization and Applications

The paper is concerned with black-box nonlinear constrained multi-objective optimization problems... more The paper is concerned with black-box nonlinear constrained multi-objective optimization problems. Our interest is the definition of a multi-objective deterministic partition-based algorithm. The main target of the proposed algorithm is the solution of a real ship hull optimization problem. To this purpose and in pursuit of an efficient method, we develop an hybrid algorithm by coupling a multi-objective DIRECT-type algorithm with an efficient derivative-free local algorithm. The results obtained on a set of "hard" nonlinear constrained multi-objective test problems show viability of the proposed approach. Results on a hull-form optimization of a high-speed catamaran (sailing in head waves in the North Pacific Ocean) are also presented. In order to consider a real ocean environment, stochastic sea state and speed are taken into account. The problem is formulated as a multi-objective optimization aimed at (i) the reduction of the expected value of the mean total resistance in irregular head waves, at variable speed and (ii) the increase of the ship operability, with respect to a set of motion-related constraints. We show that the hybrid method performs well also on this industrial problem.

Research paper thumbnail of An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints

Computational Optimization and Applications

Research paper thumbnail of Parallelized hybrid optimization methods for nonsmooth problems using NOMAD and linesearch

Computational and Applied Mathematics

Research paper thumbnail of A decomposition algorithm for unconstrained optimization problems with partial derivative information

Research Report Series of Iasi Cnr Rome Italy, 2009

In this paper we consider the problem of minimizing a nonlinear function using partial derivative... more In this paper we consider the problem of minimizing a nonlinear function using partial derivative knowledge. Namely, the objective function is such that its derivatives with respect to a pre-specified block of variables cannot be computed. To solve the problem we propose a block decomposition method that takes advantage of both derivative-free and derivative-based iterations to account for the features of the objective function. Under standard assumptions, we manage to prove global convergence of the method to stationary points of the problem.

Research paper thumbnail of A derivative-free algorithm for inequality constrained nonlinear programming

Research Report Series of Iasi Cnr Rome Italy, 2007

Research paper thumbnail of A first-order method for <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>e</mi><mi>l</mi><msub><mi>l</mi><mn>0</mn></msub></mrow><annotation encoding="application/x-tex">ell_0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8444em;vertical-align:-0.15em;"></span><span class="mord mathnormal">e</span><span class="mord mathnormal" style="margin-right:0.01968em;">l</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.01968em;">l</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3011em;"><span style="top:-2.55em;margin-left:-0.0197em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">0</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span>-penalized problems with simple constraints

Research Report Series of Iasi Cnr Rome Italy, 2012

Research paper thumbnail of Ship hydrodynamic optimization by local hybridization of deterministic derivative-free global algorithms

Applied Ocean Research, 2016

Simulation-based design optimization methods integrate computer simulations, design modification ... more Simulation-based design optimization methods integrate computer simulations, design modification tools, and optimization algorithms. In hydrodynamic applications, often objective functions are computationally expensive and noisy, their derivatives are not directly provided, and the existence of local minima cannot be excluded a priori, which motivates the use of deterministic derivative-free global optimization algorithms. The enhancement of two algorithms of this type, DIRECT (DIviding RECTangles) and DPSO (Deterministic Particle Swarm Optimization), is presented based on global/local hybridization with derivative-free line search methods. The hull-form optimization of the DTMB 5415 model is solved for the reduction of the calm-water resistance at Fr = 0.25, using potential flow and RANS solvers. Six and eleven design variables are used respectively, modifying both the hull and the sonar dome. Hybrid algorithms show a faster convergence towards the global minimum than the original global methods and are a viable option for ship hydrodynamic optimization. A significant resistance reduction is achieved both by potential flow and RANS-based optimizations, showing the effectiveness of the optimization procedure.

Research paper thumbnail of Derivative-free global ship design optimization using global/local hybridization of the DIRECT algorithm

Optimization and Engineering, 2015

A simulation-based derivative-free global optimization of the hullform of a military vessel is pr... more A simulation-based derivative-free global optimization of the hullform of a military vessel is presented, aimed at the reduction of the resistance in calm water. The objective function is of the black-box type, computationally expensive and characterized by noise and non-smoothness. The presence of local minima cannot be excluded a priori. For these reasons, the use of derivative-free, global, DIRECT-type algorithms is proposed. Specifically, a recent hybridization of the DIRECT algorithm by local minimization is applied, and compared with a novel strategy for the management of the local searches. Comparative results are reported on a set of well-known and well-established test problems and on the simulation-based hull-form optimization problem.

Research paper thumbnail of A global optimization algorithm for protein structure alignment

Research Report Series of Iasi Cnr Rome Italy, 2008

Research paper thumbnail of Global Optimization of Simulation Based Complex Systems

Operations Research/Computer Science Interfaces Series, 2015

Research paper thumbnail of Combined cycle unit commitment in a changing electricity market scenario

International Journal of Electrical Power & Energy Systems, 2015

ABSTRACT For Generation Companies (GENCOs) one of the most relevant issue is the commitment of th... more ABSTRACT For Generation Companies (GENCOs) one of the most relevant issue is the commitment of the units, the scheduling of them over a daily (or longer) time frame, with the aim of obtaining the best profit. It strongly depends on the plant operational generation costs, which depend in turn on the choices taken at the design stage; it follows that design technical choices should also aim at determining the best generation cost structure of generating units with respect to the market opportunities. In the paper the unit commitment (UC) problem has been considered, with highlights on changes in the market scenario. The paper analyzes the relevance of some design choices (structure, size, regulation type) on the economics of the operation of gas–steam combined cycle generating units. To solve the UC problem, a recently proposed method for mixed integer nonlinear programming problems, with the use of a derivative free algorithm to solve the continuous subproblems, has been considered. The results for two GENCOs are reported: one managing a single unit and the other managing three units. Numerical examples show the sensitivity of the UC solutions to the market conditions and to the design choices on the regulation type in the evolving scenario of the Italian Electricity Market.

Research paper thumbnail of Diserafino Liuzzi Piccialli Riccio Toraldo

We present a modification of the DIRECT (DIviding RECTangles) algorithm, called DIRECT-G, to solv... more We present a modification of the DIRECT (DIviding RECTangles) algorithm, called DIRECT-G, to solve a box-constrained global optimization problem arising in the detection of gravitational waves emitted by coalescing binary systems

Research paper thumbnail of Appunti del corso di Analisi delle Decisioni

Research paper thumbnail of Nonmonotone GRASP

Research paper thumbnail of Nuovi metodi per l’ottimizzazione vincolata non lineare

Research paper thumbnail of New methods for nonlinear constrained optimization

Research paper thumbnail of Unit commitment by nonlinear mixed variable programming

Research paper thumbnail of Metodi di ottimizzazione vincolata