mGPT: a probabilistic planner based on heuristic search

We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddllanguage by extracting and using different classes of lower bounds, along with various heuristic-search algorithms. The lower bounds are extracted from deterministic relaxations of the mdp where alternativeprobabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms, on the other hand, use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state with the greedy policy.

A Petri Nets-based Scheduling Methodology forMultipurpose Batch Plants.

This article presents an optimization methodology of batch production processes assembled by shared resources which rely on a mapping of state-events into time-events allowing in this way the straightforward use of a well consolidated scheduling policies developed for manufacturing systems. A technique to generate the timed Petri net representation from a continuous dynamic representation (Differential-Algebraic Equations systems (DAEs)) of the production system is presented together with the main characteristics of a Petri nets-based tool implemented for optimization purposes. This paper describes also how the implemented tool generates the coverability tree and how it can be pruned by a general purpose heuristic. An example of a distillation process with two shared batch resources is used to illustrate the optimization methodology proposed.

Heuristic procedures for solving the General Assembly Line Balancing Problem with Setups (GALBPS)

The General Assembly Line Balancing Problem with Setups (GALBPS) was recently defined in the literature. It adds sequence-dependent setup time considerations to the classical Simple Assembly Line Balancing Problem (SALBP) as follows: whenever a task is assigned next to another at the same workstation, a setup time must be added to compute the global workstation time, thereby providing the task sequence inside each workstation. This paper proposes over 50 priority-rule-based heuristic procedures to solve GALBPS, many of which are an improvement upon heuristic procedures published to date.

Testing website usability in Spanish-Speaking Academia through heuristic evaluation and cognitive walkthroughs

Although usability evaluations have been focused on assessing different contexts of use, no proper specifications have been addressed towards the particular environment of academic websites in the Spanish-speaking context of use. Considering that this context involves hundreds of millions of potential users, the AIPO Association is running the UsabAIPO Project. The ultimate goal is to promote an adequate translation of international standards, methods and ideal values related to usability in order to adapt them to diverse Spanish-related contexts of use. This article presents the main statistical results coming from the Second and Third Stages of the UsabAIPO Project, where the UsabAIPO Heuristic method (based on Heuristic Evaluation techniques) and seven Cognitive Walkthroughs were performed over 69 university websites. The planning and execution of the UsabAIPO Heuristic method and the Cognitive Walkthroughs, the definition of two usability metrics, as well as the outline of the UsabAIPO Heuristic Management System prototype are also sketched.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Optimization of KOH etching process to obtain textured substrates suitable for heterojunction solar cells fabricated by HWCVD

In this work, we have studied the texturization process of (100) c-Si wafers using a low concentration potassium hydroxide solution in order to obtain good quality textured wafers. The optimization of the etching conditions have led to random but uniform pyramidal structures with good optical properties. Then, symmetric heterojunctions were deposited by Hot-Wire CVD onto these substrates and the Quasi-Steady-State PhotoConductance technique was used to measure passivation quality. Little degradation in the effective lifetime and implicit open circuit voltage of these devices (< 20 mV) was observed in all cases. It is especially remarkable that for big uniform pyramids, the open-circuit voltage is comparable to the values obtained on flat substrates.

Design and optimization of selfnanoemulsifying drug delivery systems for enhanced dissolution of gemfibrozil

Self-nanoemulsifying drug delivery systems of gemfibrozil were developed under Quality by Design approach for improvement of dissolution and oral absorption. Preliminary screening was performed to select proper components combination. BoxBehnken experimental design was employed as statistical tool to optimize the formulation variables, X1 (Cremophor® EL), X2 (Capmul® MCM-C8), and X3 (lemon essential oil). Systems were assessed for visual characteristics (emulsification efficacy), turbidity, droplet size, polydispersity index and drug release. Different pH media were also assayed for optimization. Following optimization, the values of formulation components (X1, X2, and X3) were 32.43%, 29.73% and 21.62%, respectively (16.22% of gemfibrozil). Transmission electron microscopy demonstrated spherical droplet morphology. SNEEDS release study was compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed a significant increase in dissolution rate compared to conventional tablets. Both formulations followed Weibull mathematical model release with a significant difference in td parameter in favor of the SNEDDS. Equally amodelistic parameters were calculated being the dissolution efficiency significantly higher for SNEDDS, confirming that the developed SNEDDS formulation was superior to commercial formulation with respect to in vitro dissolution profile. This paper provides an overview of the SNEDDS of the gemfibrozil as a promising alternative to improve oral absorption.

Some optimization and decision problems in proportional reinsurance

Reinsurance is one of the tools that an insurer can use to mitigate the underwriting risk and then to control its solvency. In this paper, we focus on the proportional reinsurance arrangements and we examine several optimization and decision problems of the insurer with respect to the reinsurance strategy. To this end, we use as decision tools not only the probability of ruin but also the random variable deficit at ruin if ruin occurs. The discounted penalty function (Gerber & Shiu, 1998) is employed to calculate as particular cases the probability of ruin and the moments and the distribution function of the deficit at ruin if ruin occurs.

HouSI: Heuristic for delimitation of housing submarkets and price homogeneous areas

This paper seeks to address the problem of the empirical identification of housing market segmentation,once we assume that submarkets exist. The typical difficulty in identifying housing submarkets when dealing with many locations is the vast number of potential solutions and, in such cases, the use of the Chow test for hedonic functions is not a practical solution. Here, we solve this problem by undertaking an identification process with a heuristic for spatially constrained clustering, the"Housing Submarket Identifier" (HouSI). The solution is applied to the housing market in the city of Barcelona (Spain), where we estimate a hedonic model for fifty thousand dwellings aggregated into ten groups. In order to determine the utility of the procedure we seek to verify whether the final solution provided by the heuristic is comparable with the division of the city into ten administrative districts.

Orthologous and heterologous expression of a protein from Saccharomyces cerevisiae: Optimization for a biotechnological application

In this thesis (TFG) the results of the comparison between different methods to obtain a recombinant protein, by orthologous and heterologous expression, are exposed. This study will help us to identify the best way to express and purify a recombinant protein that will be used for biotechnology applications. In the first part of the project the goal was to find the best expression and purification system to obtain the recombinant protein of interest. To achieve this objective, a system expression in bacteria and in yeast was designed. The DNA was cloned into two different expression vectors to create a fusion protein with two different tags, and the expression of the protein was induced by IPTG or glucose. Additionally, in yeast, two promoters where used to express the protein, the one corresponding to the same protein (orthologous expression), and the ENO2 promoter (heterologous expression). The protein of interest is a NAD-dependent enzyme so, in a second time, its specific activity was evaluated by coenzyme conversion. The results of the TFG suggest that, comparing the model organisms, bacteria are more efficient than yeast because the quantity of protein obtained is higher and better purified. Regarding yeast, comparing the two expression mechanisms that were designed, heterologous expression works much better than the orthologous expression, so in case that we want to use yeast as expression model for the protein of interest, ENO2 will be the best option. Finally, the enzymatic assays, done to compare the effectiveness of the different expression mechanisms respect to the protein activity, revealed that the protein purified in yeast had more activity in converting the NAD coenzyme.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

Experimental analysis of optimization techniques on the road passenger transportation problem

Analyzing the state of the art in a given field in order to tackle a new problem is always a mandatory task. Literature provides surveys based on summaries of previous studies, which are often based on theoretical descriptions of the methods. An engineer, however, requires some evidence from experimental evaluations in order to make the appropriate decision when selecting a technique for a problem. This is what we have done in this paper: experimentally analyzed a set of representative state-of-the-art techniques in the problem we are dealing with, namely, the road passenger transportation problem. This is an optimization problem in which drivers should be assigned to transport services, fulfilling some constraints and minimizing some function cost. The experimental results have provided us with good knowledge of the properties of several methods, such as modeling expressiveness, anytime behavior, computational time, memory requirements, parameters, and free downloadable tools. Based on our experience, we are able to choose a technique to solve our problem. We hope that this analysis is also helpful for other engineers facing a similar problem