Look-ahead heuristics for the dynamic traveling purchaser problem

Given a set of products each with positive discrete demand, and a set of markets selling products at given prices, the traveling purchaser problem (TPP) looks for a tour visiting a subset of markets such that products demand is satisfied at minimum purchasing and traveling costs. In this paper we analyze a dynamic variant of the problem, where quantities may decrease as time goes on. Complete information is assumed on current state of the world, i.e. decision maker knows quantities available for each product in each market at present time and is informed about any consumption event when it occurs. Nevertheless, planner does not have any information on future events. Two groups of heuristics are described and compared. The first group consists of simplified approaches deciding which market to visit next on the basis of some greedy criteria considering only one of the two objective costs. The second one includes heuristics based on a look-ahead approach taking into account both traveling and purchasing costs and inserting some future prediction. Heuristics behavior has been tested on a large set of randomly generated instances under different levels of dynamism.     

An elitist non-dominated sorting genetic algorithm enhanced with a neural network applied to the multi-objective optimization of a polysiloxane synthesis process

This paper presents an original software implementation of the elitist non-dominated sorting genetic algorithm (NSGA-II) applied and adapted to the multi-objective optimization of a polysiloxane synthesis process. An optimized feed-forward neural network, modeling the variation in time of the main parameters of the process, was used to calculate the vectorial objective function of NSGA-II, as an enhancement to the multi-objective optimization procedure. An original technique was utilized in order to find the most appropriate parameters for maximizing the performance of NSGA-II. The algorithm provided the optimum reaction conditions (reaction temperature, reaction time, amount of catalyst, and amount of co-catalyst), which maximize the reaction conversion and minimize the difference between the obtained viscometric molecular weight and the desired molecular weight. The algorithm has proven to be able to find the entire non-dominated Pareto front and to quickly evolve optimal solutions as an acceptable compromise between objectives competing with each other. The use of the neural network makes it also suitable to the multi-objective optimization of processes for which the amount of knowledge is limited.     

On graph reasoning

In this paper, we study the (positive) graph relational calculus. The basis for this calculus was introduced by Curtis and Lowe in 1996 and some variants, motivated by their applications to semantics of programs and foundations of mathematics, appear scattered in the literature. No proper treatment of these ideas as a logical system seems to have been presented. Here, we give a formal presentation of the system, with precise formulation of syntax, semantics, and derivation rules. We show that the set of rules is sound and complete for the valid inclusions, and prove a finite model result as well as decidability. We also prove that the graph relational language has the same expressive power as a first-order positive fragment (both languages define the same binary relations), so our calculus may be regarded as a notational variant of the positive existential first-order logic of binary relations. The graph calculus, however, has a playful aspect, with rules easy to grasp and use. This opens a wide range of applications which we illustrate by applying our calculus to the positive relational calculus (whose set of valid inclusions is not finitely axiomatizable), obtaining an algorithm for deciding the valid inclusions and equalities of the latter.     

Models and Simulations for Portfolio Rebalancing

In 1950 Markowitz first formalized the portfolio optimization problem in terms of mean return and variance. Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.     

A synergistic model-driven approach for persistence modeling with UML

The Model Driven Development (MDD) approach proposes that models (and model-to-model transformations) play the main role on system development. However, there is not a consensual notation to model persistence based upon object-relational mapping frameworks: while UML lacks specific resources for persistence modeling, the entity-relationship model does not make reference to the dynamic concepts existing in UML.This paper proposes MD-JPA, a UML profile for persistence modeling based on the well-known Java Persistence API 2 (JPA) standard for object-relational mapping, pursuing the modeling of transient and persistent elements in a more coherent and synergistic way. This paper describes the main characteristics of MD-JPA as well as the way that models that adopt such profile can them be used to generate a Java implementation by the application of the proposed model transformations on a MDD approach. Finally, an open source tool was developed to make the results of this work available to the community.     

Effect of nitrogen and vanadium on austenite grain growth kinetics of a low alloy steel

Austenite grain growth kinetics in a steel containing 0.4% C, 1.8% Cr with different nitrogen contents (in the range 0.0038–0.0412%) and a micralloying addition of 0.078% V were investigated. The investigations were carried out in an austenitising temperature range of 840–1200 °C for 30 min. The results of investigations showed that N promotes the grain growth of austenite. The microalloying addition of vanadium protects the austenite grain growth because of carbonitride V(C,N) precipitation and the grain boundary pinning effect of undissolved particles of V(C,N). Using a thermodynamic model, the carbonitride V(C,N) content, undissolved at the austenitising temperature was calculated. At temperatures when a coarsening and dissolution of carbonitride occurs, the austenite grains start to growth. The effect of nitrogen on the type of chord length distribution of austenite grains was analysed.     

An exact approach for portfolio selection with transaction costs and rounds

We consider a single-period mean-safety portfolio selection problem with transaction costs and integer constraints on the quantities selected for the securities (rounds). We propose an exact approach based on the partition of the initial problem into two subproblems and the use of a simple local search heuristic to obtain an initial solution. To the best of our knowledge, no optimal algorithms have been proposed in the literature for this problem. The proposed approach is simple, general and easily adaptable to other problems. An extensive experimental analysis based on real data from the main international Stock Exchange Markets is performed. The results show, on average, an impressive improvement with respect to the computational time and space memory required by CPLEX 7.0. We also show that the solution of the first subproblem can be used on its own as an extremely effective heuristic.     

Influence of Field Effects on the Performance of InGaAs-Based Terahertz Radiation Detectors

A detailed electrical characterization of high-performance bow-tie InGaAs-based terahertz detectors is presented along with simulation results. The local surface potential and tunnelling current were scanned over the surfaces of the detectors by means of Kelvin probe force microscopy (KPFM) and scanning tunnelling microscopy (STM), which also enabled the determination of the Fermi level. Current-voltage curves were measured and modelled using the Synopsys Sentaurus TCAD package to gain deeper insight into the processes involved in detector operation. In addition, we performed finite-difference time-domain (FDTD) simulations to reveal features related to changes in the electric field due to the metal detector contacts. The investigation revealed that field-effect-induced conductivity modulation is a possible mechanism contributing to the high sensitivity of the studied detectors.     

Adhesion of resin cements to contaminated zirconia resin cements on zirconia: effect saliva-contamination and surface conditioning

This study evaluated the adhesion of resin cements to zirconia after saliva contamination using resin cements with different chemistries. Zirconia discs (N?=?240, n?=?10 per group) were randomly divided into three groups: (a) C: No contamination (Control), (b) S: Contamination with saliva, (c) S?+?AA: Contamination with saliva followed by air-abrasion (CoJet). While half of the specimens were not conditioned, the other half were conditioned with 37.5% H₃PO₄ for 60?s. After rinsing, all specimen surfaces were silanized (Monobond Plus). Resin cements based on either methacrylate (Variolink II–VL) or MDP monomer (Panavia 21-PN) were polymerized on the substrates. The specimens were randomly divided into two further groups to be tested either after (a) 24?h dry storage at 37?°C or (b) thermocycling (×5000, 5–55?°C). Microshear bond (MSB) tests were conducted in a Universal Testing Machine and failure types were analyzed. Data were analyzed using Univariate analysis and Tukey’s tests (alpha = 0.05). While saliva contamination, 37.5% H₃PO₄ application (p?<?.001) and aging (p?<?.05) significantly affected the bond results, cement type did not show significant difference after aging (p?>?.05). Adhesive strength of PN (1.2–4.4?MPa) on saliva contaminated and etched zirconia was more stable than that of VL (0–2.8?MPa). After aging, bond strength results decreased the most with VL (3–100%) compared to PN (32–71%) but the decrease was less in the air-abraded groups after aging (VL: 3%; PN: 32%). Exclusively adhesive failures were experienced in all groups.     

Preliminary Characterization of Novel Extra-cellular Lipase from Penicillium crustosum Under Solid-State Fermentation and its Potential Application for Triglycerides Hydrolysis

Current studies about lipase production involve the use of agro-industrial residues and newly isolated microorganisms aimed at increasing economic attractiveness of the process. Based on these aspects, the main objective of this work is to perform the partial characterization of enzymatic extracts produced by a newly isolated Penicillium crustosum in solid-state fermentation. Lipase extract presented optimal temperature and pH of 37?°C and 9?C10, respectively. The concentrated enzymatic extract showed more stability at 25?°C and pH?7. The enzymes kept 100% of their enzymatic activity until 60?days of storage at 4 and ?10?°C. The stability under calcium salts indicated that the hydrolytic activity presented decay with the increase of calcium concentration. The specificity under several substrates indicated good enzyme activities in triglycerides from C4 to C18.