•Large herbivores strongly impact forest renewal through browsing.•Spatial and temporal variation in browsing may reflect changes in ungulate density.•Browsing probability was investigated in the ...Italian Alps, in several populations of red deer.•Browsing responded to red deer density at different spatial scales.•The effect of density was mediated by shrub species richness.•Density is a strong predictor of browsing intensity, supporting the potential for cascading effects.
Large herbivores can profoundly influence terrestrial ecosystems. Through browsing, for example, they can impact forest regeneration with consequences for both plant and animal species. Understanding the drivers of ungulate browsing is therefore crucial from a conservation and management standpoint. Browsing is generally thought to be affected by ungulate density, such that increased density leads to greater browsing probability. As a result, browsing has been suggested as an indicator of ungulate density. While most studies investigated long-term browsing impact of ungulates in single study areas, few of them focused on different spatial scales using multiple replications in time and space. In this study we took advantage of 25 years of browsing data within the Stelvio National Park (central Italian Alps) derived from several populations of red deer and modelled the ratio of browsing on conifers (calculated as browsed conifers divided by total number of conifers) as a function of two different density indices at different spatial scales and a set of environmental covariates. Specifically, we investigated whether variations in red deer density at different spatial scales reflect variations in browsing probability. The results suggest that as deer density increased, the ratio of browsing increased at all spatial scales, at times mediated by shrub species diversity. Density was a consistent driver of browsing probability within all deer populations, while the effect of confounding variables was statistically unclear as they yielded conflicting results for the different populations, failing to find common patterns. This study highlights that density at different spatial scale is an important predictor of browsing probability, suggesting that browsing could be a reliable indicator of variations in ungulate density. In turn, as browsing can map small- and large-scale density variations, pattern of browsing impact may be a useful tool to investigate small- and large-scale changes in red deer densities due to disturbance factors such as human activities or the presence of large predators.
Stable isotope analyses of bone collagen are often used in palaeoecological studies to reveal environmental conditions in the habitats of different herbivore species. However, such studies require ...valuable reference data, obtained from analyses of modern individuals, in habitats of well-known conditions. In this article, we present the stable carbon and nitrogen isotope composition of bone collagen from modern red deer (N = 242 individuals) dwelling in various habitats (N = 15 study sites) in Europe. We investigated which of the selected climatic and environmental factors affected the delta.sup.13 C and delta.sup.15 N values in bone collagen of the studied specimens. Among all analyzed factors, the percent of forest cover influenced the carbon isotopic composition most significantly, and decreasing forest cover caused an increase in delta.sup.13 C values. The delta.sup.15 N was positively related to the proportion of open area and (only in the coastal areas) negatively related to the distance to the seashore. Using rigorous statistical methods and a large number of samples, we confirmed that delta.sup.13 C and delta.sup.15 N values can be used as a proxy of past habitats of red deer.
•An optimization model is proposed for a dual-channel closed-loop supply chain network design.•The model captures the fuzzy nature of the parameters.•The Jimenez’s method is used to defuzzify the ...original model.•Two new hybrid meta-heuristics are proposed for the problem.•A real-life case study for the tire industry in Iran is performed.
There is so much interest in online purchasing within supply chain networks nowadays. After expanding the internet access and services, customers’ behavior has changed. Today, a customer’s shopping manner usually begins with the internet search. With this approach, we face some new trends in this field, such as online-to-offline (O2O) commerce that aims to balance online and offline sales. Regarding the supply chain management, the O2O commerce can help the managers to conduct both online and offline businesses. The tire industry is one of the applications of the O2O approach, which also directly affects the supply chain network design (SCND). Therefore, this work for the first time proposes a dual-channel, multi-product, multi-period, multi-echelon closed-loop SCND under uncertainty for the tire industry. To tackle the uncertain parameters of the problem (e.g., prices and demand), a fuzzy approach, so-called the Jimenez’s method, is applied. Another main innovation of this work is two new hybrid meta-heuristic algorithms with new procedures. Two recent nature-inspired algorithms (i.e., red deer algorithm (RDA) and whale optimization algorithm (WOA)) are hybridized with the genetic algorithm (GA) and simulated annealing (SA) to strengthen the diversification and intensification phases, respectively. The numerical experiments demonstrate that the hybrid version of WOA and SA returns high-quality solutions and requires an acceptable amount of computational time. The conducted sensitivity analyses underline the importance of tire remanufacturing. Furthermore, setting the appropriate prices in different channels for the available tire types is critical for sustainable tire supply chain management.
While the partial shading operation is observed in the photovoltaic (PV) panel, the solar radiation strikes the PV modules placed in a non-homogeneous PV array. Most of the array reconfiguration ...approaches for PV arrays use puzzle-based mathematical techniques to relocate the PV modules. While taking size as the parameter, the existing array reconfiguration approach is not a reliable option for efficient shaded dispersion in large-scale sized PV arrays. The main intent of this paper is to implement a novel array reconfiguration model in PV systems using improved an hybrid meta-heuristic algorithm. In the proposed model, the optimal array reconfiguration is attained by a hybrid meta-heuristic algorithm called Red Deer-Moth-Flame Optimization (RD-MFO), which can prove its excellence in providing the optimal PV array. The proposed objective model with best array reconfiguration is focused on a multi-objective function that covers the constraints like maximizing the power, minimizing efficiency, and minimizing shading loss, and other constraints like fill factor, income generation, and mismatch losses. To validate the reconfiguration model, the proposed approach has experimented on a 9 × 9 PV array with four shade patterns. Furthermore, the comparative analysis of attaining the multi-objective function by the proposed RD-MFO over the conventional meta-heuristic algorithm proves the efficiency of the proposed arrangement. While considering the efficiency of the designed RD-MFO-based PV array for case 4 is 16.923% improved than IPM and 19.230% improved than SGDA. Thus, all the computations have been verified with all the methods, and the suggested model gets superior performance in PV array reconfiguration.
Nature has been considered as an inspiration of several recent meta-heuristic algorithms. This paper firstly studies and mimics the behavior of Scottish red deer in order to develop a new ...nature-inspired algorithm. The main inspiration of this meta-heuristic algorithm is to originate from an unusual mating behavior of Scottish red deer in a breading season. Similar to other population-based meta-heuristics, the red deer algorithm (RDA) starts with an initial population called red deers (RDs). They are divided into two types: hinds and male RDs. Besides, a harem is a group of female RDs. The general steps of this evolutionary algorithm are considered by the competition of male RDs to get the harem with more hinds via roaring and fighting behaviors. By solving 12 benchmark functions and important engineering as well as multi-objective optimization problems, the superiority of the proposed RDA shows in comparison with other well-known and recent meta-heuristics.
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This study provides a three-objective mixed-integer linear mathematical model to design a sustainable closed-loop supply chain network in the aluminum industry. In this regard, the proposed model ...optimizes economic, social, and environmental objectives simultaneously. The main contribution of this research is to provide a framework for the sustainable aluminum supply chain in Iran by applying the life cycle assessment (LCA) to estimate the environmental impacts and using two novel meta-heuristic algorithms to optimize the proposed mathematical model. In this regard, the multi-objective gray wolf optimizer (MOGWO), the multi-objective red deer algorithm (MORDA), and augmented epsilon constraint (AEC) are used to achieve Pareto optimal solutions. Comparisons between solutions methods show that the MOGWO algorithm and MORDA have a very high advantage over the AEC method in terms of the scatter of Pareto solutions. Moreover, the statistical tests indicate that the MORDA has an advantage over MOGWO in terms of Pareto boundary diversification as well as the quality of solutions. On the other hand, results of the implementation in the aluminum industry show that increasing the coefficient of recycled materials' use in the production of secondary aluminum has a significant impact on the Pareto boundary and leads to reducing production costs and in particular the reduction of carbon dioxide emissions.
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