A methodology to simulate peak water demand for water supply systems using semi-direct methods: A case study for a residential building in Mexico.

Historically, approaches for determining peak water demand in buildings have been based on probabilistic methods. Extensive research has shown that these methods lack accuracy because of the human factor in the probability of use. Inaccuracy in the calculation of peak water demand is the main cause of oversized water supply systems in buildings. This has led to unfavorable effects such as: 1) increasing the building carbon footprint due to the use of more construction materials, and 2) engendering health hazards due to the stagnation of water causing microbial growing. This paper presents a step-by-step methodology that serves to calculate the peak water demand by simulating the use of plumbing fixtures based on data obtained from standardized flowrate. With the implementation of the methodology, the peak water demand estimated was 2.6 times lower in comparison to traditional methods. The main conclusion drawn from the research is the potential of the methodology to easily simulated peak water demand in residential buildings in the short term. Thus, it reveals a hotspot for peak water demand calculation and can serve as routes for future research.

Femicide in Mexico: Statistical evidence of an increasing trend.

This study analyzes whether femicide in Mexico has increased more severely than other life and bodily integrity crimes (e.g., homicide, culpable homicide, injuries, malicious injuries, abortion, and other crimes that threaten life). To achieve this, the Executive Secretariat of the National Public Security System database was cleaned and the number of femicides per 100,000 inhabitants was calculated, for the period from January 2016 to March 2022 in all states of Mexico. Through descriptive statistics, non-parametric analysis of means, and hypothesis tests, we demonstrate that the states with the highest number of femicides are the Estado de Mexico (State of Mexico), Ciudad de Mexico (Mexico City), and Veracruz; moreover, the number of femicides exhibits a growing trend while the total number of life and bodily integrity crimes does not. Finally, we forecast the number of femicides for the next five months. To our knowledge, there is no other article that analyzes the growth trend of femicide compared to other crimes. Visualizing and understanding that femicide is on the rise compared with other types of crimes can help the government and legislators generate policies that are consistent with the magnitude of the problem.

Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.

In this article two multi-stage stochastic linear programming models are developed, one applying the stochastic programming solver integrated by Lingo 17.0 optimization software that utilizes an approximation using an identical conditional sampling and Latin-hyper-square techniques to reduce the sample variance, associating the probability distributions to normal distributions with defined mean and standard deviation; and a second proposed model with a discrete distribution with 3 values and their respective probabilities of occurrence. In both cases, a scenario tree is generated. The models developed are applied to an aggregate production plan (APP) for a furniture manufacturing company located in the state of Hidalgo, Mexico, which has important clients throughout the country. Production capacity and demand are defined as random variables of the model. The main purpose of this research is to determine a feasible solution to the aggregate production plan in a reasonable computational time. The developed models were compared and analyzed. Moreover, this work was complemented with a sensitivity analysis; varying the percentage of service level, also, varying the stochastic parameters (mean and standard deviation) to test how these variations impact in the solution and decision variables.

Solution to travelling salesman problem by clusters and a modified multi-restart iterated local search metaheuristic.

This article finds feasible solutions to the travelling salesman problem, obtaining the route with the shortest distance to visit n cities just once, returning to the starting city. The problem addressed is clustering the cities, then using the NEH heuristic, which provides an initial solution that is refined using a modification of the metaheuristic Multi-Restart Iterated Local Search MRSILS; finally, clusters are joined to end the route with the minimum distance to the travelling salesman problem. The contribution of this research is the use of the metaheuristic MRSILS, that in our knowledge had not been used to solve the travelling salesman problem using clusters. The main objective of this article is to demonstrate that the proposed algorithm is more efficient than Genetic Algorithms when clusters are used. To demonstrate the above, both algorithms are compared with some cases taken from the literature, also a comparison with the best-known results is done. In addition, statistical studies are made in the same conditions to demonstrate this fact. Our method obtains better results in all the 10 cases compared.