Decisional Variables Research Articles

Optimizing Energy Consumption of Industrial Robots with Model-Based Layout Design

The paper describes the development of an optimization model for the layout of an industrial robot relative to known locations of served machines and operations to be performed. Robotized material handling applications, defined by trajectories (paths, speed profiles) and final points, are considered in this research. An energy-monitoring framework set up by joint velocities provides input data that are fed to the optimization model. The physical placement of the robot base stands for the decisional variables, while the objective function is represented by the total distance covered by individual joints along established task routes transposed into energy consumption. The values of the decisional variables are restricted by trajectory constraints (waypoints on paths), joint operating values and link dimensions. Modelling technique and practical results using the Microsoft Solver optimization tool from Excel for Microsoft 365, Version 2312 are reported for SCARA-type robots. The performance of the optimization model is compared with actual measurements of consumed energy on an Adept Cobra S600 SCARA robot.

The AddACO: A bio-inspired modified version of the ant colony optimization algorithm to solve travel salesman problems

The Travel Salesman Problem (TSP) consists in finding the minimal-length closed tour that connects the entire group of nodes of a given graph. We propose to solve such a combinatorial optimization problem with the AddACO algorithm: it is a version of the Ant Colony Optimization method that is characterized by a modified probabilistic law at the basis of the exploratory movement of the artificial insects. In particular, the ant decisional rule is here set to amount in a linear convex combination of competing behavioral stimuli and has therefore an additive form (hence the name of our algorithm), rather than the canonical multiplicative one. The AddACO intends to address two conceptual shortcomings that characterize classical ACO methods: (i) the population of artificial insects is in principle allowed to simultaneously minimize/maximize all migratory guidance cues (which is in implausible from a biological/ecological point of view) and (ii) a given edge of the graph has a null probability to be explored if at least one of the movement trait is therein equal to zero, i.e., regardless the intensity of the others (this in principle reduces the exploratory potential of the ant colony). Three possible variants of our method are then specified: the AddACO-V1, which includes pheromone trail and visibility as insect decisional variables, and the AddACO-V2 and the AddACO-V3, which in turn add random effects and inertia, respectively, to the two classical migratory stimuli. The three versions of our algorithm are tested on benchmark middle-scale TPS instances, in order to assess their performance and to find their optimal parameter setting. The best performing variant is finally applied to large-scale TSPs, compared to the naive Ant-Cycle Ant System, proposed by Dorigo and colleagues, and evaluated in terms of quality of the solutions, computational time, and convergence speed. The aim is in fact to show that the proposed transition probability, as long as its conceptual advantages, is competitive from a performance perspective, i.e., if it does not reduce the exploratory capacity of the ant population w.r.t. the canonical one (at least in the case of selected TSPs). A theoretical study of the asymptotic behavior of the AddACO is given in the appendix of the work, whose conclusive section contains some hints for further improvements of our algorithm, also in the perspective of its application to other optimization problems.

Shared decision making in patients with substance use disorders: A one-year follow-up study

Patient-centered care in therapeutic processes has been associated with better clinical outcomes, however, it remains a poorly studied aspect in Substance Use Disorder (SUD). The study aimed to evaluate patient's preferences, perceived participation in treatment decisions and activation level; and how they predict retention, pharmacological adherence and substance use during one-year follow-up. Logistic regression models were used to analyze the association between independent variables, along with a wide number of sociodemographic and clinical covariates, and outcomes. Most patients prefer a shared or passive role when making decisions about their treatment, and showed concordance between their preferred and perceived roles. In the univariate models, perceiving more involvement than desired showed a higher likelihood of treatment discontinuation at 12 months, and substance use at 6 and 12 months. No significant associations were found between the remaining decisional variables or the degree of activation with the assessed outcomes. A majority of SUD patients prefer and perceive to be involved in the decision-making process about their treatment. Patients perceiving more involvement than desired might experience an excess of responsibility that could negatively influence treatment continuation and substance use. Limitations of the study preclude any definitive conclusion, and more research is needed to confirm these results.

An Exact Approach for Selecting Pickup-Delivery Stations in Urban Areas to Reduce Distribution Emission Costs

This paper deals with a variant of the multifacility location-routing problem in urban areas. The distribution network is modelled by an undirected graph, in which the nodes are split into a set of pickup-delivery stations, a depot, and a set of customers. The arcs represent the minimum-cost connections between nodes. A customer is assigned to a pickup-delivery station if he or she can reach it at the lowest sustainable cost, i.e., on foot or by bicycle, without exceeding a predefined maximum distance. The goal is to minimise the goods’ total delivery cost, including pollutant emissions. In this perspective, both travel distance and means of transport play a key role. We present an exact novel approach based on partitioning the research space of the solutions of a Mixed Integer Linear Programming model. In the model, Boolean decisional variables, representing the selection of the locations for the pickup-delivery stations, are fixed simultaneously with the solution of the classical Travelling Salesman Problem. A branching constraint allows us to determine the route that serves the selected pickup-delivery stations and the route, if any, that serves customers who do not go to any pickup-delivery station. We conduct extensive experimentation to test the proposed approach’s computational efficiency and analyse the optimal solution’s robustness with respect to the maximum distance of customers from the stations, their activation cost and the pollutant emissions. The effectiveness of the proposed approach in terms of solution quality and computation time is certified by a set of computational tests based on randomly generated instances with up to 150 customers and 30 pickup-delivery stations. The application of the proposed exact method to a case study related to a district of the city of Genoa (Italy) confirms its validity also for sustainably addressing real-size urban delivery problems. An evaluation of incentives for customers using pickup-delivery stations, possibly by implementing discount policies on orders, is also proposed.

A Method to Design Assembling Lines for Super Premium Efficiency Motors

Producing highly efficient electric motors remains a challenge nowadays. Given that the legislation in the field requires the transition to the production of engines with increased efficiency, for manufacturing companies, switching from one generation of engines to another can be a difficult task. This paper analyzes ways to adapt the assembly of engines of the IE4 generation starting from the assembly lines of the engines of the previous generation, IE3. The analysis of the assembly process covers both the operator training part and the actual assembly part. Ten possible variants for the assembly line and specific decisional variables have been defined. The decision to choose the optimal assembly configuration was made using as management tools the matrix of consequences and utilities. The validation of the theoretical model of the assembly line was carried out through a case study built for two classes of electric motors, namely G90 and G180. For a total production of IE4 electric motors of 20,000 parts/month, the analyzed variants, respectively, the two sizes (G90 and G100) represent 35% (7000 parts/month) of the G90 size and 22% (4400 parts/month) the G100 size. The aim is to provide a new modular assembly concept, which depending on the orders, can use, as given in the conclusion of this article.

Thermo-economic optimization of a multi-source (air/sun/ground) residential heat pump with a water/PCM thermal storage

The main target of this paper is to numerically study a multi-source (air/sun/ground) heat pump with the implementation of a thermal energy storage, using either water or PCM, for residential space heating. The system was modelled considering several sub-models for each of the components (compressor, solar panels, storage tank, heat exchangers etc.). A control strategy has been established to decide which operating mode of the system provides the highest coefficient of performance (COP). A multi-objective optimization through genetic algorithm of several decisional variables of the system was carried out, in different configurations and climate conditions, by considering different scenarios in terms of total investment and energy consumption costs, to optimize seasonal performances and investment cost of the entire system. Results show that solar thermal and solar photovoltaic collectors coupled with water storage tank give higher seasonal energy performance, especially in warmer climates, whereas the exploitation of the ground source can be more advantageous for colder climates. From the optimization analysis, it results that optimal non-dominated solutions characterized by a SCOP increase between 50% and 250% are characterized by higher investment costs between 215% and 730%, depending on the climate conditions. None of the solutions employing a PCM storage tank results economically feasible, due to a slight effect on system performance, and a much higher effect on investment costs. Finally, several cost scenarios in terms of incentives on investment costs and increased energy prices were analysed, for which the employment of scenarios with higher capital investment can be more advantageous in terms of lower total costs.

Sustainability assessment of different land tenure farming systems in tea farming: The effect of decisional and structural variables.

This study focuses on the sustainability of different land tenure farms in tea farming and explores the effect of structural and decisional variables on tea farm sustainability. For this, a total of 138 tea growers from the Rize province of Turkey were selected through a stratified sampling approach and interviewed directly. The positive and negative effects of independent variables on all dimensions of sustainability were emphasized after an extensive review of the literature. This reviewing activity also facilitated hypothesizing the possible influences of variables on overall tea sustainability. A tobit model was used to examine the influence of the structural and decisional variables on tea farm sustainability. The results described that owners were more sustainable compared with shareholders. Their economic and social sustainability levels were not significantly different from each other. However, environmental sustainability at owners' tea farms was more satisfactory than that of shareholders. Among structural variables, land slope, age of tea orchard, and farmers' age were negative influences, whereas cooperative membership and terrace status affected tea farm sustainability positively. Similarly, among decisional variables, family labor, fertilizer application methods, farmers' willingness to perform a soil test, and sale value of tea had positive influences, whereas the cost of chemical fertilizers had a negative influence on tea farm sustainability. The land tenure was found to have a significant effect on sustainability when the tea farmer was the owner of the farm. Thus, farmers should replant their orchards on time, and adopt sustainable practices such as terracing and employing environment-friendly fertilizer application methods for increasing tea sustainability in the locality. Integr Environ Assess Manag 2021;17:814-834. © 2020 SETAC.

Pupillary Dilations of Mice Performing a Vibrotactile Discrimination Task Reflect Task Engagement and Response Confidence.

Pupillometry, the measure of pupil size and reactivity, has been widely used to assess cognitive processes. Changes in pupil size have been shown to correlate with various behavioral states, both externally and internally induced such as locomotion, arousal, cortical state, and decision-making processes. Besides, these pupillary responses have also been linked to the activity of neuromodulatory systems that modulate attention and perception such as the noradrenergic and cholinergic systems. Due to the extent of processes the pupil reflects, we aimed at further resolving pupillary responses in the context of behavioral state and task performance while recording pupillary transients of mice performing a vibrotactile two-alternative forced-choice task (2-AFC). We show that before the presentation of task-relevant information, pre-stimulus, pupil size differentiates between states of disengagement from task performance vs. engagement. Also, when subjects have to attend to task stimuli to attain a reward, post-stimulus, pupillary dilations exhibit a difference between correct and error responses with this difference reflecting an internal decision variable. We hypothesize that this internal decision variable relates to response confidence, the internal perception of the confidence the subject has in its choice. As opposed to this, we show that in a condition of passive performance, when the stimulus has no more task relevance due to reward being provided automatically, pupillary dilations reflect the occurrence of stimulation and reward provision but not decisional variables as under active performance. Our results provide evidence that in addition to reflecting attentiveness under task performance rather than arousal per se, pupil dilations also reflect the confidence of the subject in his ensuing response. This confidence coding is overlaid within a more pronounced pupil dilation that reflects post-decision components that are related to the response itself but not to the decision. We also provide evidence as to how different behavioral states, imposed by task demands, modulate what the pupil is reflecting, presumably showing what the underlying cognitive network is coding for.

Auditory cortex reflects goal-directed movement but is not necessary for behavioral adaptation in sound-cued reward tracking.

Mounting evidence suggests that the role of sensory cortices in perceptual decision making goes beyond the mere representation of the discriminative stimuli and additionally involves the representation of nonsensory variables such as reward expectation. However, the relevance of these representations for behavior is not clear. To address this issue, we trained rats to discriminate sounds in a single-interval forced-choice task and then confronted the animals with unsignaled blockwise changes of reward probabilities. We found that unequal reward probabilities for the two choice options led to substantial shifts in response bias without concomitant reduction in stimulus discrimination. Although decisional biases were on average less extreme than required to maximize overall reinforcement, a model-based analysis revealed that rats managed to harvest >97% of rewards. Neurons in auditory cortex recorded during task performance weakly differentiated the discriminative stimuli but more strongly the subsequent goal-directed movement. Although 10-20% of units exhibited significantly different firing rates between task epochs with different response biases, control experiments showed this to result from inflated false positive rates due to unspecific temporal correlations of spiking activity rather than changing reinforcement contingencies. Transient pharmacological inactivation of auditory cortex reduced sound discriminability without affecting other measures of performance, whereas inactivation of medial prefrontal cortex affected both discriminability and bias. Together, these results suggest that auditory cortex activity only weakly reflects decisional variables during flexible updating of stimulus-response-outcome contingencies and does not play a crucial role in sound-cued adaptive behavior, beyond the representation of the discriminative stimuli.NEW & NOTEWORTHY Recent evidence suggests that sensory cortex represents nonsensory variables such as reward expectation, but the relevance of these representations for behavior is not well understood. We show that rat auditory cortex (AC) is modulated during movement and reward anticipation in a sound-cued reward tracking task, whereas AC inactivation only impaired discrimination without affecting reward tracking, consistent with a predominantly sensory role of AC.

Racial/ethnicity differences when endorsing influential factors for prostate cancer treatment choice: An analysis of data from the personal patient profile-prostate (P3P) I and II trials.

351 Background: Race and ethnicity impact the type of treatment received for localized prostate cancer in American men. We hypothesized that there may be differences in men’s influential values and preferences related to treatment decisions. Methods: We analyzed samples from two multicenter, randomized trials of the Patient Profile-Prostate (P3P) decision aid, first comparing the trial groups on demographic and decisional variables using Chi-square tests. Stratified (P3P I vs II) logistic regression was then used to assess the univariate association between race/ethnicity and endorsement of moderate-or-strong influence of 14 lifestyle factors, current or future symptoms, or important others on the decision. A multivariable stratified logistic regression with backward variable selection was used to further estimate the association between influential factors and race/ethnicity. Results: Data from 494 and 392 participants in P3PI and P3PII, respectively, were analyzed for 40 Hispanic, 168 non-Hispanic black, 637 non-Hispanic white, 19 others and 6 missing. Age (p=.0001), education (p<.0001), marital status (p<.0001), income (p<.0001), Internet use for information (p<.0001) and decisional control preference were significantly different across racial/ethnic groups. In adjusted analyses, racial/ethnic differences existed for influence of age (Non Hispanic Black (NHB) vs. Non Hispanic White (NHW) OR: 0.56 95%CI 0.38-0.85p=.002), religion/spirituality (NHB vs. NHW OR: 3.2095%CI1.95-5.26, p<.0001), future bladder function (NHB vs. NHW OR: 0.5795%CI0.35-0.90, p=.04), future ability to engage in recreation (NHB vs. NHW OR: 0.5495%CI 0.34-0.86, p=0.02), and a story of a famous person with prostate cancer (NHB vs. NHW OR: 2,11 95%CI1.30-3.43, p=.007). Conclusions: Our results suggest racial/ethnic differences for influences underlying treatment choice. Better understanding these influences may help us present salient information about treatment options to patients and address disparities.

Racial/ethnicity differences in endorsing influential factors for prostate cancer treatment choice: An analysis of data from the personal patient profile-prostate (P3P) I and II trials

ObjectiveRates and choice of treatment for localized prostate cancer vary according to race/ethnicity in American men. We hypothesized that there were group differences in influential values and preferences related to treatment decisions. MethodsWe analyzed samples from 2 multicenter, randomized trials of the Patient Profile-Prostate (P3P) I and II decision aid, first comparing the groups on other demographic and decisional variables using Chi-square tests. Stratified (P3P I vs. II) logistic regression was then used to assess the univariate association between race/ethnicity and endorsement of moderate-or-strong influence of 14 lifestyle factors, current or future symptoms, or important others on the decision. A multivariable stratified logistic regression with backward variable selection was used to further estimate the association between influential factors and race/ethnicity. ResultsThere were 494 and 392 participants in P3P I and P3P II, respectively, with 40 Hispanic, 168 non-Hispanic black, 637 non-Hispanic white, 19 others and 6 missing. Age (P = 0.0001), education (P < 0.0001), marital status (P < 0.0001), income (P < 0.0001), Internet use for information (P < 0.0001) and decisional control preference were significantly different across racial/ethnic groups. In adjusted analyses, we saw racial/ethnic differences in the decisional influence of age (Non-Hispanic Black (NHB) vs. Non-Hispanic White (NHW) OR: 0.56 95%CI 0.38–0.85 P = 0.002), religion/spirituality (NHB vs. NHW OR: 3.2095%CI1.95–5.26, P < 0.0001), future bladder function (NHB vs. NHW OR: 0.5795%CI 0.35–0.90, P = 0.04), future ability to engage in recreation (NHB vs. NHW OR: 0.5495%CI 0.34–0.86, P = 0.02), and a story of a famous person with prostate cancer (NHB vs. NHW OR: 2,11 95%CI 1.30–3.43, P = 0.007). No interactions were found. ConclusionOur results suggest racial/ethnic differences for influences underlying treatment choice. Better understanding these influences may help us present salient information about treatment options to patients and address disparities.

Optimal Control of the Mean Field Equilibrium for a Pedestrian Tourists’ Flow Model

Art heritage cities are popular tourist destinations but for many of them overcrowding is becoming an issue. In this paper, we address the problem of modeling and analytically studying the flow of tourists along the narrow alleys of the historic center of a heritage city. We initially present a mean field game model, where both continuous and switching decisional variables are introduced to respectively describe the position of a tourist and the point of interest that he/she may visit. We prove the existence of a mean field equilibrium. A mean field equilibrium is Nash-type equilibrium in the case of infinitely many players. Then, we study an optimization problem for an external controller who aims to induce a suitable mean field equilibrium.

Decision on Institutional Choice in the Healthcare Sector: Micro-empirical Evidences from West Bengal (India)

An attempt has been made in this article to shed some light on the decisions of patients on their institutional choice in accessing healthcare services within micro empirical framework in the state of West Bengal, India. The determinants of such decisions are also recognized in this article. In conscientious, statistical methods are anticipated to frame the socio-economic and decisional variables, that influence the decision. Principal component analysis and ordered probit analysis have been deployed to scrutinize the same. It is observed that the economic status of the patients, their level of schooling, their income and some other decision variables have a strong influence on their access of healthcare institutions. The study has projected that intra-category and inter-category competition among available alternative service providers needs to be introduced and social entrepreneurship model in state-owned hospitals can be pioneered with due considerations.

Techno-Economic Design of Wind Farms: A Methodology and Multi-Scenario Application

This paper aims to present a methodology and multi-scenario application for the techno-economic assessment of the wind turbine layout in a wind farm. The considered decisional variables deal with the number of wind turbines to install, their self-distance and their distance toward the primary grid line. In addition, the wind speed profile and the site boundary environmental conditions are within the methodology. The levelized cost of energy (LCOE) and the net present value (NPV) are estimated as the key results and decisional indicators to compare multiple scenarios within two relevant locations in the Middle East (a case study of Abadan site in Iran) and the Mediterranean region (a case study of Swatar site in Malta). Finally, for each site, an effective layout of the wind farm is selected. Numerical results lead to the optimum layout with the lowest cost of energy. Swatar site has the highest potential of wind for the energy production. The LCOE for this site is estimated to be 4.01 c€/kWh for a wind farm with a size of 10 MW and 5.76 c€/kWh for a wind farm with size of 25 MW. Overall, it is shown that the wind power fosters sustainable development in both case studies and the proposed structures and layouts increase the performances of the wind farms, considerably.

Randomised controlled trial of a repeated consultation support intervention for patients with colorectal cancer.

UK healthcare policy for improving cancer outcomes supports participation of patients in care decisions with clinicians. Consultation Planning, Recording and Summarising (CPRS) has shown evidence of increasing patient decision self-efficacy, reducing uncertainty, and regret of decisions. This is the first trial of CPRS within the colorectal cancer population and delivered over serial medical consultations. This randomised controlled trial compared usual care to the addition of CPRS over consecutive oncology consultations with newly diagnosed colorectal cancer (CRC) patients in Edinburgh, Scotland. The study primarily evaluated patients' perception of their decision self-efficacy, preparation for decision-making, decisional conflict, and decisional regret, with secondary measures of anxiety and depression. Compared with usual care, overall, the intervention group reported significantly higher decision self-efficacy (P=0.001) and preparation for decision-making (P<0.001) and significantly lower decisional conflict (P=0.018) and regret (P=0.039). The repeated intervention patients felt significantly better prepared for each consultation (P<0.05); reported higher DSE before (P=0.05) and after (P=0.031) consultation one, and after consultation three (P=0.004); and reported lower decisional conflict after consultation two (P=0.007). Analyses comparing groups over time on decisional variables and anxiety and depression were underpowered because of attrition. Among colorectal cancer patients, CPRS was associated with decisional benefits before and after each consultation and 3months after the last consultation. It appears that CPRS patients began their first medical consultation on a better trajectory but did not widen the gap over time. More research is needed on the benefits of CPRS being administered once or consecutively.

Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system’s Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72kWh, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.

Female entrepreneurs: motivations and constraints. An Italian regional study

Purpose This paper aims to identify the specific contextual constraints that women might face in becoming entrepreneurs; to correlate these constraints with the motivations that have determined this choice; and to ascertain how strongly constraints and motivations are correlated with individual rewards in terms of personal satisfaction and economic payoffs. Design/methodology/approach The empirical base is a survey that the authors conducted among female entrepreneurs in a Southern province of Italy in 2012. Data are analyzed through a correspondence and cluster analysis. The socio-economic context of the province within which these female-led firms operate is taken into account by means of a correspondence canonical analysis. Findings In terms of results: first, two-thirds of female entrepreneurs in the province are positively motivated, and this is a determining factor in their choice to become entrepreneurs. This translates into they also being satisfied with the choice they made. Second, contrary to the expectations, being positively motivated and satisfied holds both for firms operating in more dynamic and demanding sectors and for small firms using little financial or human capital. Research limitations/implications The chosen research approach has allowed to identify the most important decisional variables that affect female entrepreneurial choice. However, as most of the variables are categorical, the research’s results remain descriptive. Practical implications Positive motivations and personal rewards are clearly relevant for women making an entrepreneurial choice. However, they are not enough to stimulate fully the potential for growth of their enterprises: education and a social environment conducive to female creative expression are also necessary. To this end, the authors suggest that an important function of change could be played in particular by universities by fostering a culture of creativity and entrepreneurship. Social implications By stressing the connections between positive motivations and wellbeing, the authors suggest that the promotion of women’s entrepreneurial choices through networks and education generates more than purely economic benefits. It also has positive effects on their quality of life and on social welfare as well. Originality/value This paper responds to a need – not yet fulfilled in the literature – to better understand the relations between women’s motivation, satisfaction and the type of business selected.

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous than classic selection, provided that GS is already initiated (i.e. the initial reference population is available). Optimizing decisional variables of the classic selection scheme could be of greater benefit than including genomic information in optimized designs.

Multiobjective Optimization of Pipe Replacements and Control Valve Installations for Leakage Attenuation in Water Distribution Networks

This paper shows how pipe replacements and control valve installations can be optimized in water distribution networks to reduce leakage, under minimum nodal pressure constraints. To this end, a hybrid multiobjective algorithm, which has pipe diameters and valve positions and settings as decisional variables, was set up. The algorithm also enables identification of the isolation valves that have to be closed in order to improve effectiveness of the control valves installed. The algorithm is initially applied to the optimal valve location problem, where it explores the trade-off between the number of installed control valves and the daily leakage volume. In this context, the analysis of the results proves the new algorithm more effective than a multiobjective genetic algorithm widely adopted in the scientific literature. Furthermore, it shows that if some isolation valves identified ad hoc are closed in the network, the installation of control valves determines larger leakage volume reductions. In a second application of the algorithm, pipe replacements and control valve installations are simultaneously performed. In this case, a Pareto front of trade-off solutions between installation costs and daily leakage volume is obtained. For the choice of the final solution within the front, an economic criterion based on the long-term convenience analysis is also illustrated.

Pareto Optimal Multi-Objective Optimization of Antiwear Tialn/Tin/Cr Coatings

ABSTRACT The multi-objective optimization procedure of geometry of TiAlN/TiN/Cr multilayer coatings was created. The procedure was applied to the multilayer coatings subjected to constant tangential and normal loads (Hertzian contact). In physical model Cr, TiN and TiAlN layers were treated as a continuous medium, thus in mathematical description of the stress and strain states in the coatings a classical theory of stiffness was used. Decisional variables used in procedure were thicknesses of Cr, TiN and TiAlN layers and decisional criteria were functions of the stress and strain fields in the coating and substrate. Using created optimization procedure, Pareto set of optimal values of layers' thicknesses were determined. Additionally, two methods of analysis of Pareto-optimal set were introduced and discussed.