Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives

The properties of local optimal solutions in multi-objective combinatorial optimization problems are crucial for the effectiveness of local search algorithms, particularly when these algorithms are based on Pareto dominance. Such local search algorithms typically return a set of mutually nondominated Pareto local optimal (PLO) solutions, that is, a PLO-set. This paper investigates two aspects of PLO-sets by means of experiments with Pareto local search (PLS). First, we examine the impact of several problem characteristics on the properties of PLO-sets for multi-objective NK-landscapes with correlated objectives. In particular, we report that either increasing the number of objectives or decreasing the correlation between objectives leads to an exponential increment on the size of PLO-sets, whereas the variable correlation has only a minor effect. Second, we study the running time and the quality reached when using bounding archiving methods to limit the size of the archive handled by PLS, and thus, the maximum size of the PLO-set found. We argue that there is a clear relationship between the running time of PLS and the difficulty of a problem instance.Comment: appears in Parallel Problem Solving from Nature - PPSN XIII, Ljubljana : Slovenia (2014

Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives

The properties of local optimal solutions in multi-objective combinatorial optimization problems are crucial for the effectiveness of local search algorithms, particularly when these algorithms are based on Pareto dominance. Such local search algorithms typically return a set of mutually nondominated Pareto local optimal (PLO) solutions, that is, a PLO-set. This paper investigates two aspects of PLO-sets by means of experiments with Pareto local search (PLS). First, we examine the impact of several problem characteristics on the properties of PLO-sets for multi-objective NK-landscapes with correlated objectives. In particular, we report that either increasing the number of objectives or decreasing the correlation between objectives leads to an exponential increment on the size of PLO-sets, whereas the variable correlation has only a minor effect. Second, we study the running time and the quality reached when using bounding archiving methods to limit the size of the archive handled by PLS, and thus, the maximum size of the PLO-set found. We argue that there is a clear relationship between the running time of PLS and the difficulty of a problem instance.Comment: appears in Parallel Problem Solving from Nature - PPSN XIII, Ljubljana : Slovenia (2014

Ecos del XIX International Botanical Congress

Del 23 al 29 de juliol d’enguany va tenir lloc a Shenzhen (província de Guangdong, Xina) el XIX International Botanical Congress (IBC), el principal simposi del món dedicat a la botànica, i que se celebra cada sis anys. L’IBC va estar organitzat conjuntament per la Societat Botànica de la Xina i el govern de la Municipalitat de Shenzhen. Una setmana abans del congrés, del 17 al 21 de juliol, va tenir lloc la reunió de la Secció de Nomenclatura de l’IBC a la Ciutat Universitària de Shenzhen, amb l’objectiu principal de revisar el codi internacional de nomenclatura.Peer reviewe

Optical emission from Si O2 -embedded silicon nanocrystals: A high-pressure Raman and photoluminescence study

© 2015 American Physical Society. We investigate the optical properties of high-quality Si nanocrystals (NCs)/SiO2 multilayers under high hydrostatic pressure with Raman scattering and photoluminescence (PL) measurements. The aim of our study is to shed light on the origin of the optical emission of the Si NCs/SiO2. The Si NCs were produced by chemical-vapor deposition of Si-rich oxynitride (SRON)/SiO2 multilayers with 5- and 4-nm SRON layer thicknesses on fused silica substrates and subsequent annealing at 1150°C, which resulted in the precipitation of Si NCs with an average size of 4.1 and 3.3 nm, respectively. From the pressure dependence of the Raman spectra we extract a phonon pressure coefficient of 8.5±0.3cm-1/GPa in both samples, notably higher than that of bulk Si(5.1cm-1/GPa). This result is ascribed to a strong pressure amplification effect due to the larger compressibility of the SiO2 matrix. In turn, the PL spectra exhibit two markedly different contributions: a higher-energy band that redshifts with pressure, and a lower-energy band which barely depends on pressure and which can be attributed to defect-related emission. The pressure coefficients of the higher-energy contribution are (-27±6) and (-35±8)meV/GPa for the Si NCs with a size of 4.1 and 3.3 nm, respectively. These values are sizably higher than those of bulk Si(-14meV/GPa). When the pressure amplification effect observed by Raman scattering is incorporated into the analysis of the PL spectra, it can be concluded that the pressure behavior of the high-energy PL band is consistent with that of the indirect transition of Si and, therefore, with the quantum-confined model for the emission of the Si NCs.Work supported by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 245977 (project NASCEnT). Financial support by the Spanish Government through projects LEOMIS (TEC2012-38540-C02-01) and MAT2012-38664-C02-02 is also acknowledgedPeer Reviewe

The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches

This work deals with the so-called weighted independent domination problem, which is an $NP$-hard combinatorial optimization problem in graphs. In contrast to previous work, this paper considers the problem from a non-theoretical perspective. The first contribution consists in the development of three integer linear programming models. Second, two greedy heuristics are proposed. Finally, the last contribution is a population-based iterated greedy metaheuristic which is applied in two different ways: (1) the metaheuristic is applied directly to each problem instance, and (2) the metaheuristic is applied at each iteration of a higher-level framework---known as construct, merge, solve \& adapt---to sub-instances of the tackled problem instances. The results of the considered algorithmic approaches show that integer linear programming approaches can only compete with the developed metaheuristics in the context of graphs with up to 100 nodes. When larger graphs are concerned, the application of the populated-based iterated greedy algorithm within the higher-level framework works generally best. The experimental evaluation considers graphs of different types, sizes, densities, and ways of generating the node and edge weights

The weighted independent domination problem: ILP model and algorithmic approaches

This work deals with the so-called weighted independent domination problem, which is an N P -hard combinatorial optimization problem in graphs. In contrast to previous theoretical work from the liter- ature, this paper considers the problem from an algorithmic perspective. The first contribution consists in the development of an integer linear programming model and a heuristic that makes use of this model. Sec- ond, two greedy heuristics are proposed. Finally, the last contribution is a population-based iterated greedy algorithm that takes profit from the better one of the two developed greedy heuristics. The results of the compared algorithmic approaches show that small problem instances based on random graphs are best solved by an efficient integer linear programming solver such as CPLEX. Larger problem instances are best tackled by the population-based iterated greedy algorithm. The experimental evaluation considers random graphs of different sizes, densities, and ways of generating the node and edge weights

Optical emission from SiO2-embedded silicon nanocrystals: a high pressure Raman and photoluminescence study

We investigate the optical properties of high-quality Si nanocrystals (NCs)/SiO2 multilayers under high hydrostatic pressure with Raman scattering and photoluminescence (PL) measurements. The aim of our study is to shed light on the origin of the optical emission of the Si NCs/SiO2. The Si NCs were produced by chemical-vapor deposition of Si-rich oxynitride (SRON)/SiO2 multilayers with 5- and 4-nm SRON layer thicknesses on fused silica substrates and subsequent annealing at 1150 °C, which resulted in the precipitation of Si NCswith an average size of 4.1 and 3.3 nm, respectively. From the pressure dependence of the Raman spectra we extract a phonon pressure coefficient of 8.5 ± 0.3 cm−1/GPa in both samples, notably higher than that of bulk Si (5.1 cm−1/GPa). This result is ascribed to a strong pressure amplification effect due to the larger compressibility of the SiO2 matrix. In turn, the PL spectra exhibit two markedly different contributions: a higher-energy band that redshifts with pressure, and a lower-energy band which barely depends on pressure and which can be attributed to defect-related emission. The pressure coefficients of the higher-energy contribution are (−27 ± 6) and (−35 ± 8) meV/GPa for the Si NCs with a size of 4.1 and 3.3 nm, respectively. These values are sizably higher than those of bulk Si (−14 meV/GPa). When the pressure amplification effect observed by Raman scattering is incorporated into the analysis of the PL spectra, it can be concluded that the pressure behavior of the high-energy PL band is consistent with that of the indirect transition of Si and, therefore, with the quantum-confined model for the emission of the Si NCs

Accurate and efficient constrained molecular dynamics of polymers using Newton's method and special purpose code

In molecular dynamics simulations we can often increase the time step by imposing constraints on bond lengths and bond angles. This allows us to extend the length of the time interval and therefore the range of physical phenomena that we can afford to simulate. We examine the existing algorithms and software for solving nonlinear constraint equations in parallel and we explain why it is necessary to advance the state-of-the-art. We present ILVES-PC, a new algorithm for imposing bond constraints on proteins accurately and efficiently. It solves the same system of differential algebraic equations as the celebrated SHAKE algorithm, but ILVES-PC solves the nonlinear constraint equations using Newton’s method rather than the nonlinear Gauss-Seidel method. Moreover, ILVES-PC solves the necessary linear systems using a specialized linear solver that exploits the structure of the protein. ILVES-PC can rapidly solve constraint equations as accurately as the hardware will allow. The run-time of ILVES-PC is proportional to the number of constraints. We have integrated ILVES-PC into GROMACS and simulated proteins of different sizes. Compared with SHAKE, we have achieved speedups of up to 4.9× in single-threaded executions and up to 76× in shared-memory multi-threaded executions. Moreover, ILVES-PC is more accurate than P-LINCS algorithm. Our work is a proof-of-concept of the utility of software designed specifically for the simulation of polymers