From Genetic Algorithms to Efficient Organization

The work described in this thesis began as an inquiry into the nature and use of optimization programs based on "genetic algorithms." That inquiry led, eventually, to three powerful heuristics that are broadly applicable in gradient-ascent programs: First, remember the locations of local maxima and restart the optimization program at a place distant from previously located local maxima. Second, adjust the size of probing steps to suit the local nature of the terrain, shrinking when probes do poorly and growing when probes do well. And third, keep track of the directions of recent successes, so as to probe preferentially in the direction of most rapid ascent. These algorithms lie at the core of a novel optimization program that illustrates the power to be had from deploying them together. The efficacy of this program is demonstrated on several test problems selected from a variety of fields, including De Jong's famous test-problem suite, the traveling salesman problem, the problem of coordinate registration for image guided surgery, the energy minimization problem for determining the shape of organic molecules, and the problem of assessing the structure of sedimentary deposits using seismic data.

Continuous GRASP with a local active-set method for bound-constrained global optimization

Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a hybrid heuristic-based on the CGRASP and GENCAN methods-for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate the relative effectiveness of CGRASP-GENCAN on a set of benchmark multimodal test functions.

Optimization Of Groundwater Remediation With New Efficient Parallel Algorithm For Global Optimization

Application of optimization algorithm to PDE modeling groundwater remediation can greatly reduce remediation cost. However, groundwater remediation analysis requires a computational expensive simulation, therefore, effective parallel optimization could potentially greatly reduce computational expense. The optimization algorithm used in this research is Parallel Stochastic radial basis function. This is designed for global optimization of computationally expensive functions with multiple local optima and it does not require derivatives. In each iteration of the algorithm, an RBF is updated based on all the evaluated points in order to approximate expensive function. Then the new RBF surface is used to generate the next set of points, which will be distributed to multiple processors for evaluation. The criteria of selection of next function evaluation points are estimated function value and distance from all the points known. Algorithms created for serial computing are not necessarily efficient in parallel so Parallel Stochastic RBF is different algorithm from its serial ancestor. The application for two Groundwater Superfund Remediation sites, Umatilla Chemical Depot, and Former Blaine Naval Ammunition Depot. In the study, the formulation adopted treats pumping rates as decision variables in order to remove plume of contaminated groundwater. Groundwater flow and contamination transport is simulated with MODFLOW-MT3DMS. For both problems, computation takes a large amount of CPU time, especially for Blaine problem, which requires nearly fifty minutes for a simulation for a single set of decision variables. Thus, efficient algorithm and powerful computing resource are essential in both cases. The results are discussed in terms of parallel computing metrics i.e. speedup and efficiency. We find that with use of up to 24 parallel processors, the results of the parallel Stochastic RBF algorithm are excellent with speed up efficiencies close to or exceeding 100%.

A cost optimization-based design of precast concrete floors using genetic algorithms

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A comparison about evolutionary algorithms for optimum-path forest clustering optimization

In this paper we deal with the problem of boosting the Optimum-Path Forest (OPF) clustering approach using evolutionary-based optimization techniques. As the OPF classifier performs an exhaustive search to find out the size of sample's neighborhood that allows it to reach the minimum graph cut as a quality measure, we compared several optimization techniques that can obtain close graph cut values to the ones obtained by brute force. Experiments in two public datasets in the context of unsupervised network intrusion detection have showed the evolutionary optimization techniques can find suitable values for the neighborhood faster than the exhaustive search. Additionally, we have showed that it is not necessary to employ many agents for such task, since the neighborhood size is defined by discrete values, with constrain the set of possible solution to a few ones.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.

Parameters and algorithms to evaluate cardiac mechanics by conductance catheter

This work is structured as follows: In Section 1 we discuss the clinical problem of heart failure. In particular, we present the phenomenon known as ventricular mechanical dyssynchrony: its impact on cardiac function, the therapy for its treatment and the methods for its quantification. Specifically, we describe the conductance catheter and its use for the measurement of dyssynchrony. At the end of the Section 1, we propose a new set of indexes to quantify the dyssynchrony that are studied and validated thereafter. In Section 2 we describe the studies carried out in this work: we report the experimental protocols, we present and discuss the results obtained. Finally, we report the overall conclusions drawn from this work and we try to envisage future works and possible clinical applications of our results. Ancillary studies that were carried out during this work mainly to investigate several aspects of cardiac resynchronization therapy (CRT) are mentioned in Appendix. -------- Ventricular mechanical dyssynchrony plays a regulating role already in normal physiology but is especially important in pathological conditions, such as hypertrophy, ischemia, infarction, or heart failure (Chapter 1,2.). Several prospective randomized controlled trials supported the clinical efficacy and safety of cardiac resynchronization therapy (CRT) in patients with moderate or severe heart failure and ventricular dyssynchrony. CRT resynchronizes ventricular contraction by simultaneous pacing of both left and right ventricle (biventricular pacing) (Chapter 1.). Currently, the conductance catheter method has been used extensively to assess global systolic and diastolic ventricular function and, more recently, the ability of this instrument to pick-up multiple segmental volume signals has been used to quantify mechanical ventricular dyssynchrony. Specifically, novel indexes based on volume signals acquired with the conductance catheter were introduced to quantify dyssynchrony (Chapter 3,4.). Present work was aimed to describe the characteristics of the conductancevolume signals, to investigate the performance of the indexes of ventricular dyssynchrony described in literature and to introduce and validate improved dyssynchrony indexes. Morevoer, using the conductance catheter method and the new indexes, the clinical problem of the ventricular pacing site optimization was addressed and the measurement protocol to adopt for hemodynamic tests on cardiac pacing was investigated. In accordance to the aims of the work, in addition to the classical time-domain parameters, a new set of indexes has been extracted, based on coherent averaging procedure and on spectral and cross-spectral analysis (Chapter 4.). Our analyses were carried out on patients with indications for electrophysiologic study or device implantation (Chapter 5.). For the first time, besides patients with heart failure, indexes of mechanical dyssynchrony based on conductance catheter were extracted and studied in a population of patients with preserved ventricular function, providing information on the normal range of such a kind of values. By performing a frequency domain analysis and by applying an optimized coherent averaging procedure (Chapter 6.a.), we were able to describe some characteristics of the conductance-volume signals (Chapter 6.b.). We unmasked the presence of considerable beat-to-beat variations in dyssynchrony that seemed more frequent in patients with ventricular dysfunction and to play a role in discriminating patients. These non-recurrent mechanical ventricular non-uniformities are probably the expression of the substantial beat-to-beat hemodynamic variations, often associated with heart failure and due to cardiopulmonary interaction and conduction disturbances. We investigated how the coherent averaging procedure may affect or refine the conductance based indexes; in addition, we proposed and tested a new set of indexes which quantify the non-periodic components of the volume signals. Using the new set of indexes we studied the acute effects of the CRT and the right ventricular pacing, in patients with heart failure and patients with preserved ventricular function. In the overall population we observed a correlation between the hemodynamic changes induced by the pacing and the indexes of dyssynchrony, and this may have practical implications for hemodynamic-guided device implantation. The optimal ventricular pacing site for patients with conventional indications for pacing remains controversial. The majority of them do not meet current clinical indications for CRT pacing. Thus, we carried out an analysis to compare the impact of several ventricular pacing sites on global and regional ventricular function and dyssynchrony (Chapter 6.c.). We observed that right ventricular pacing worsens cardiac function in patients with and without ventricular dysfunction unless the pacing site is optimized. CRT preserves left ventricular function in patients with normal ejection fraction and improves function in patients with poor ejection fraction despite no clinical indication for CRT. Moreover, the analysis of the results obtained using new indexes of regional dyssynchrony, suggests that pacing site may influence overall global ventricular function depending on its relative effects on regional function and synchrony. Another clinical problem that has been investigated in this work is the optimal right ventricular lead location for CRT (Chapter 6.d.). Similarly to the previous analysis, using novel parameters describing local synchrony and efficiency, we tested the hypothesis and we demonstrated that biventricular pacing with alternative right ventricular pacing sites produces acute improvement of ventricular systolic function and improves mechanical synchrony when compared to standard right ventricular pacing. Although no specific right ventricular location was shown to be superior during CRT, the right ventricular pacing site that produced the optimal acute hemodynamic response varied between patients. Acute hemodynamic effects of cardiac pacing are conventionally evaluated after stabilization episodes. The applied duration of stabilization periods in most cardiac pacing studies varied considerably. With an ad hoc protocol (Chapter 6.e.) and indexes of mechanical dyssynchrony derived by conductance catheter we demonstrated that the usage of stabilization periods during evaluation of cardiac pacing may mask early changes in systolic and diastolic intra-ventricular dyssynchrony. In fact, at the onset of ventricular pacing, the main dyssynchrony and ventricular performance changes occur within a 10s time span, initiated by the changes in ventricular mechanical dyssynchrony induced by aberrant conduction and followed by a partial or even complete recovery. It was already demonstrated in normal animals that ventricular mechanical dyssynchrony may act as a physiologic modulator of cardiac performance together with heart rate, contractile state, preload and afterload. The present observation, which shows the compensatory mechanism of mechanical dyssynchrony, suggests that ventricular dyssynchrony may be regarded as an intrinsic cardiac property, with baseline dyssynchrony at increased level in heart failure patients. To make available an independent system for cardiac output estimation, in order to confirm the results obtained with conductance volume method, we developed and validated a novel technique to apply the Modelflow method (a method that derives an aortic flow waveform from arterial pressure by simulation of a non-linear three-element aortic input impedance model, Wesseling et al. 1993) to the left ventricular pressure signal, instead of the arterial pressure used in the classical approach (Chapter 7.). The results confirmed that in patients without valve abnormalities, undergoing conductance catheter evaluations, the continuous monitoring of cardiac output using the intra-ventricular pressure signal is reliable. Thus, cardiac output can be monitored quantitatively and continuously with a simple and low-cost method. During this work, additional studies were carried out to investigate several areas of uncertainty of CRT. The results of these studies are briefly presented in Appendix: the long-term survival in patients treated with CRT in clinical practice, the effects of CRT in patients with mild symptoms of heart failure and in very old patients, the limited thoracotomy as a second choice alternative to transvenous implant for CRT delivery, the evolution and prognostic significance of diastolic filling pattern in CRT, the selection of candidates to CRT with echocardiographic criteria and the prediction of response to the therapy.

Optimization of thin noise barrier designs using Evolutionary Algorithms and a Dual BEM Formulation

[EN]This works aims at assessing the acoustic efficiency of differente this noise barrier models. These designs frequently feature complex profiles and their implementarion in shape optimization processes may not always be easy in terms of determining their topological feasibility. A methodology to conduct both overall shape and top edge optimisations of thin cross section acoustic barriers by idealizing them as profiles with null boundary thickness is proposed.

Application of evolutionary algorithms and the boundary element method in the optimization of noise barrier profiles

[EN]This Ph.D. thesis presents a general, robust methodology that may cover any type of 2D acoustic optimization problem. A procedure involving the coupling of Boundary Elements (BE) and Evolutionary Algorithms is proposed for systematic geometric modifications of road barriers that lead to designs with ever-increasing screening performance. Numerical simulations involving single- and multi-objective optimizations of noise barriers of varied nature are included in this document. results disclosed justify the implementation of this methodology by leading to optimal solutions of previously defined topologies that, in general, greatly outperform the acoustic efficiency of classical, widely used barrier designs normally erected near roads.

Tetrahedral mesh optimization combining boundary and inner node relocation and adaptive local refinement

[EN]This work introduces a new technique for tetrahedral mesh optimization. The procedure relocates boundary and inner nodes without changing the mesh topology. In order to maintain the boundary approximation while boundary nodes are moved, a local refinement of tetrahedra with faces on the solid boundary is necessary in some cases. New nodes are projected on the boundary by using a surface parameterization. In this work, the proposed method is applied to tetrahedral meshes of genus-zero solids that are generated by the meccano method. In this case, the solid boundary is automatically decomposed into six surface patches which are parameterized into the six faces of a cube with the Floater parameterization...

Algorithms and Models For Combinatorial Optimization Problems

In this thesis we present some combinatorial optimization problems, suggest models and algorithms for their effective solution. For each problem,we give its description, followed by a short literature review, provide methods to solve it and, finally, present computational results and comparisons with previous works to show the effectiveness of the proposed approaches. The considered problems are: the Generalized Traveling Salesman Problem (GTSP), the Bin Packing Problem with Conflicts(BPPC) and the Fair Layout Problem (FLOP).