This paper presents a hybrid genetic algorithm with collective communication (HGACC) using distributed processing for the job shop scheduling problem. The genetic algorithm starts with a set of elite micro-populations created randomly, where the fitness of these individuals does not exceed a tuned upper bound in the makespan value. The computational processes distribute the micro-populations collectively. In the micro-populations, each individual's search for good solutions is directed toward the solution space of the fittest individual, identified by an approximation of genetic traits. In each generation of the genetic algorithm, the best individual from each micro-population migrates to another micro-population to maintain diversity in populations. Changes in the genetic sequence are applied to each individual by the simulated annealing algorithm (iterative mutation). In this paper, the results obtained show that the genetic algorithm achieves excellent results, as compared to other genetic algorithms. It is also better than other non-genetic meta heuristics or competes with them.

This study reports for the first time the isolation, identification and characterization of lipase-producing thermophilic strain from the geothermal water of the El Chichón volcano crater lake. Two strains were identified by 16S rRNA sequencing as Geobacillus jurassicus CHI2 and Geobacillus stearothermophilus CHI1. Results showed that G. jurassicus CHI2 is Gram-positive, able to ferment maltose, fructose and sucrose and to hydrolyze starch and casein; while G. stearothermophilus CHI1 showed to be Gram-variable, able to ferment maltose and fructose and to hydrolyze starch. Colonies of both strains presented irregular shape, umbilicated elevation of gummy texture and cells presented flagellar movement to survive in fluids with high temperature and mass gradients due to complex phenomena of heat and mass transfer present in the geothermal fluids. Lipase production for G. stearothermophilus CHI1 was also evaluated. It was found that this strain possesses a growth associated with extracellular lipase production with a high activity of 143 U/mL at 8.3 h of incubation time, superior to the activities reported for other microorganisms of genus Geobacillus; for this reason, it can be said that the thermal flow of the El Chichón volcano crater lake can be a useful source of lipase-producing thermophilic bacteria.

This paper describes one grid-based genetic algorithm approach to solve the vehicle routing problem with time windows in one experimental cluster MiniGrid. Clusters used in this approach are located in two Mexican cities (Cuernavaca and Jiutepec, Morelos) securely communicating with each other since they are configured as one virtual private network, and its use as a single set of processors instead of isolated groups allows one to increase the computing power to solve complex tasks. The genetic algorithm splits the population of candidate solutions in several segments, which are simultaneously mutated in each process generated by the MiniGrid. These mutated segments are used to build a new population combining the results produced by each process. In this paper, the MiniGrid configuration scheme is described, and both the communication latency and the speedup behavior are discussed. Experimental results show one information exchange reduction through the MiniGrid clusters as well as an improved behavior of the evolutionary algorithm. A statistical analysis of these results suggests that our approach is better as a combinatorial optimization procedure as compared with other methods.

This paper presents an educational mobile assistant application for type 1 diabetes patients. The proposed application is based on four mathematical models that describe the glucose-insulin-glucagon dynamics using a compartmental model, with additional equations to reproduce aerobic exercise, gastric glucose absorption by the gut, and subcutaneous insulin absorption. The medical assistant was implemented in Java and deployed and validated on several smartphones with Android OS. Multiple daily doses can be simulated to perform intensive insulin therapy. As a result, the proposed application shows the influence of exercise periods, food intakes, and insulin treatments on the glucose concentrations. Four parameter variations are studied, and their corresponding glucose concentration plots are obtained, which show agreement with simulators of the state of the art. The developed application is focused on type-1 diabetes, but this can be extended to consider type-2 diabetes by modifying the current mathematical models.

Heat exchangers play an important role in different industrial processes; therefore, it is important to characterize these devices to improve their efficiency by guaranteeing the efficient use of energy. In this study, we carry out a numerical analysis of flow dynamics, heat transfer, and entropy generation inside a heat exchanger; an aqueous medium used for oil extraction flows through the exchanger. Hot water flows on the shell side; nanoparticles have been added to the water in order to improve heat transfer toward the cold aqueous medium flowing on the tube side. The aqueous medium must reach a certain temperature in order to obtain its oil extraction properties. The analysis is performed for different Richardson numbers (Ri = 0.1–10), nanofluid volume fractions (φ = 0.00–0.06), and heat exchanger heights (H = 0.6–1.0). Results are presented in terms of Nusselt number, total entropy generation, Bejan number, and performance evaluation criterion. Results showed that heat exchanger performance increases with the increase in Ri when Ri > 1 and when reducing H.

Around the world there have recently been new and more powerful computing platforms created that can be used to work with computer science problems. Some of these problems that are dealt with are real problems of the industry; most are classified by complexity theory as hard problems. One such problem is the vehicle routing problem with time windows (VRPTW). The computational Grid is a platform which has recently ventured into the treatment of hard problems to find the best solution for these. This chapter presents a genetic algorithm for the vehicle routing problem with time windows. The algorithm iteratively applies a mutation operator, first of the intelligent type and second of the restricting type. The algorithm takes advantage of Grid computing to increase the exploration and exploitation of the solution space of the problem. The Grid performance is analyzed for a genetic algorithm and a measurement of the latencies that affect the algorithm is studied. The convenience of applying this new computing platform to the execution of algorithms specially designed for Grid computing is presented.

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This paper presents a numerical analysis of entropy generation in a two-dimensional rectangular channel where the inlet flow undergoes thermal decomposition resulting from a chemical reaction. The model considered viscosity and thermal conductivity to be dependent of temperature. Irreversibility due to mass transport was included in the entropy generation analysis. Relevant applications of this study are possible for the design of power generation systems and reactors. The effects of the Reynolds number, Schmidt number, and length of the heat source on thermal fluid dynamics, mass transfer, and irreversibility were also investigated. It was found that thermal decomposition increases at: a) low Reynolds numbers, b) low Schmidt numbers, and c) increased length of heat source. Additionally, overall entropy generation increased when Reynolds number and length of heat source were increased, although in all cases, overall irreversibility attains a minimum value at a specific Schmidt number.