A procedure to size solar-powered irrigation (photoirrigation) schemes

The high cost of photovoltaic solar power makes it necessary, before undertaking any subsequent study, to dimension photovoltaic installations as accurately as possible. We here present a procedure to estimate the required dimension of a photovoltaic installation designed to power a pumping system for the drip irrigation of an olive tree orchard in SW Spain. The method consists of three main stages: (1) One determines the irrigation requirements of the specific estate according to the characteristics of its soil-type and climate. (2) A hydraulic analysis of the pumping system is made according to the depth of the aquifer and the height needed to stabilize the pressure in the water distribution network. (3) Finally, one determines the peak photovoltaic power required to irrigate a 10 ha sub-plot of the estate taking into account the overall yield of the photovoltaic-pump-irrigation system.We call this arrangement “photoirrigation”, and believe that it may be of great utility to improve the output of such socially significant crops as olives and wine grapes, optimizing the use of water and solar energy resources at the same time as preserving the environment.     

Relation between food habits and nutritional status of preschool children in a rural community

Food habits in regard to the nutritional status of preschool children and their socioeconomic situation were analyzed in this research. The study was carried out in Cuetzalan, State of Puebla; all families were studied and, besides the presence of a preschool child in the home, both father and mother should also be living in the same house. Forty children considered as well nourished and 40 malnourished in the opposite case, were selected, taking the limits of the Gómez classification. In order to define socioeconomic differences between the two groups, the sample population was divided into different levels, with the following results. The socioeconomic level of the well-nourished children did correlate with a good living standard of their families; in the other case, families with a low socioeconomic status, presented more nutritional problems. A questionnaire was applied to every mother selected. This included two items: a) In the first case, we tried to assess the mother's attitude towards food habits and children's illnesses. b) In the second case, the mother's knowledge concerning pregnancy, breast feeding, feeding of the child during the first year of life, taboos, beliefs and other aspects which could be related to nutrition. On the whole, the main objective of this study was attained, because significant differences were found between these two groups. Firstly, a good relationship between food habits and good nutritional status of the children was found. Secondly, mother with well-nourished children had better food habits and better socioeconomic status than mothers having children with poor health status, and therefore, of a lower socioeconomic status.     

Evolutionary multiobjective optimization using an outranking-based dominance generalization

One aspect that is often disregarded in the current research on evolutionary multiobjective optimization is the fact that the solution of a multiobjective optimization problem involves not only the search itself, but also a decision making process. Most current approaches concentrate on adapting an evolutionary algorithm to generate the Pareto frontier. In this work, we present a new idea to incorporate preferences into a multi-objective evolutionary algorithm (MOEA). We introduce a binary fuzzy preference relation that expresses the degree of truth of the predicate “x is at least as good as y”. On this basis, a strict preference relation with a reasonably high degree of credibility can be established on any population. An alternative x is not strictly outranked if and only if there does not exist an alternative y which is strictly preferred to x. It is easy to prove that the best solution is not strictly outranked. For validating our proposed approach, we used the non-dominated sorting genetic algorithm II (NSGA-II), but replacing Pareto dominance by the above non-outranked concept. So, we search for the non-strictly outranked frontier that is a subset of the Pareto frontier. In several instances of a nine-objective knapsack problem our proposal clearly outperforms the standard NSGA-II, achieving non-outranked solutions which are in an obviously privileged zone of the Pareto frontier.     

A simple multimembered evolution strategy to solve constrained optimization problems

This work presents a simple multimembered evolution strategy to solve global nonlinear optimization problems. The approach does not require the use of a penalty function. Instead, it uses a simple diversity mechanism based on allowing infeasible solutions to remain in the population. This technique helps the algorithm to find the global optimum despite reaching reasonably fast the feasible region of the search space. A simple feasibility-based comparison mechanism is used to guide the process toward the feasible region of the search space. Also, the initial stepsize of the evolution strategy is reduced in order to perform a finer search and a combined (discrete/intermediate) panmictic recombination technique improves its exploitation capabilities. The approach was tested with a well-known benchmark. The results obtained are very competitive when comparing the proposed approach against other state-of-the art techniques and its computational cost (measured by the number of fitness function evaluations) is lower than the cost required by the other techniques compared.     

Asymptotic convergence of metaheuristics for multiobjective optimization problems

This paper analyzes the convergence of metaheuristics used for multiobjective optimization problems in which the transition probabilities use a uniform mutation rule. We prove that these algorithms converge only if elitism is used.     

Effect of manganese(II) on the respiratory activity of biological sludge from wastewater treatment plant

The aim of this study was to determine the effect of manganese(II) on the respiratory activity and cellular metabolism of activated sludge from two different wastewater treatment plants (WWTP). The tested manganese concentrations were: 0.5, 1, 1.5, 2, 4 and 6 mg/L. The effect of this heavy metal on endogenous metabolism was studied by determining the specific endogenous respiration rate (SOUR_endo), chemical oxygen demand (COD) and measures of enzymatic activity (dehydrogenase activity), while the effect on the biodegradation capacity was determined through the terminal velocity of oxygen consumption (OUR_exo). Measurements were taken at 30 min, 3 h and 24 h of exposure of the sludge to the heavy metal. The results showed that concentrations below 1 ppm produce an increase in the respiratory activity of both sludges. Increasing the concentration of manganese (≥2 mg/L) resulted in substantial reductions in respiratory activity, being more significant for long exposure times. Finally, it was observed that activation of the endogenous respiration rate at low concentrations of manganese during the first hours of the test produces greater stabilization of the sludge, as identified by a lower terminal velocity of synthetic wastewater degradation and lower values of COD measured in the supernatant.     

Multiobjective optimization of trusses using genetic algorithms

In this paper we propose the use of the genetic algorithm (GA) as a tool to solve multiobjective optimization problems in structures. Using the concept of min–max optimum, a new GA-based multiobjective optimization technique is proposed and two truss design problems are solved using it. The results produced by this new approach are compared to those produced by other mathematical programming techniques and GA-based approaches, proving that this technique generates better trade-offs and that the genetic algorithm can be used as a reliable numerical optimization tool.