Management Scheme Research Articles

Optimized Multi‐Scale Attention Convolutional Neural Network for Micro‐Grid Energy Management System Employing in Internet of Things

ABSTRACTThe combination of micro‐grid energy management systems (EMSs) with the Internet of Things (IoT) offers a promising way to improve energy use and distribution. However, challenges such as device compatibility and the difficulty of managing energy efficiently make it hard to implement these systems effectively. This study offers a significant advancement in energy management by using IoT for microgrid systems. An Optimized Multi‐scale Attention Convolutional Neural Network for microgrid EMS employing IoT (OMACNN‐MGEMS‐IoT) is proposed in this study, which enables efficient monitoring and control of energy resources. The proposed model's input data are gathered from the MQTT dataset. This research employs a Regularized Bias‐aware Ensemble Kalman Filter (RBAEKF) for pre‐processing input data, ensuring the removal of outliers and updating missing values. The MACNN is then used for effective fault detection within the microgrid. To enhance its performance, the Sheep Flock Optimization Algorithm (SFOA) is introduced to optimize the MACNN parameters, ensuring accurate fault detection. Implemented on the MATLAB platform, the performance of the OMACNN‐MGEMS‐IoT method is assessed through various performance metrics, demonstrating significant improvements. Notably, the proposed method achieves higher cost reductions of 25%, 22%, and 26% compared to existing approaches such as the IoT platform for energy management in multi‐micro grid systems (IoT‐PEM‐MMS), a micro‐grid system infrastructure implementing IoT for efficient energy management in buildings (MSII‐IoT‐EEM) and a hybrid deep learning‐based online energy management scheme for industrial microgrids (HDL‐OEM‐IM). The findings highlight the impact of the proposed OMACNN‐MGEMS‐IoT method in enhancing energy efficiency and cost‐effectiveness in microgrid systems.

Occupational risk factors for sleep quality among Serbian airline pilots

IntroductionThe ability of airline pilots to maintain a good level of sleep goes a long way in ensuring operational effectiveness with regard to safety as well as personal health. The study assesses the risk factors for sleep quality of airline pilots in Serbia with the objective of determining those factors, both occupational and lifestyle that are paramount in assisting with sleep health.MethodsA cross-sectional study was conducted on a total of 66 Serbian commercial pilots, and the Pittsburgh Sleep Quality Index (PSQI) was used to assess their sleep quality. Demographic, occupational, lifestyle, biological and psychological variables were obtained through validated questionnaires. Multivariate logistic regression was used to determine the predictors of poor sleep quality (PSQI ≥5).ResultsOverall sleep quality was poor in 65.2% of the participants. Significant factors associated with poor sleep quality included years of experience (OR = 1.17, p = 0.007) and levels of stress (OR = 2.87, p = 0.004). Particular lifestyle variables, including factors such as coffee intake, had initial relationships with sleep quality but were not significant in the multivariate models. With regard to age, a significant univariate association was also revealed but was dropped in the final model because of collinearity with years of experience.ConclusionSerbian commercial pilots have a relatively high risk of inadequate sleep associated with years of experience and levels of stress. There is a need to implement organization-wide changes such as stress management schemes in order to improve sleep quality among pilots, and foster prioritizing well-being.

Accommodation–repelling fields for mitigating human–goose conflicts

AbstractResearch Highlight discussing: Seltmann, M., Ylitalo, A.K., Piironen, A., Store, R., Heikkinen, J., Heim, W., Piha, M., Seimola, T., Laaksonen, T., & Forsman, J. (2024). Arctic migrating barnacle geese utilize accommodation fields in a new agricultural staging area. Journal of Applied Ecology, https://doi.org/10.1111/1365‐2664.14838. Human–wildlife conflicts often involve wildlife damage affecting people's livelihoods. Many goose species have increased due to conservation efforts and agriculture practices. Their preference to forage intensively in agricultural areas has caused large‐scale damage to farmland, creating a conflict that needs effective mitigation solutions. Seltmann et al. investigated the effectiveness of accommodation‐and‐repelling‐field mitigation strategy by looking at habitat selection of satellite‐tracked barnacle geese (Branta leucopsis) at regional and local scales in an agricultural area of high goose impact. They found that geese at both scales preferred accommodation fields assigned in the study, suggesting the effectiveness of this management scheme in farmer–goose conflict mitigation. Their research highlighted the needs for refining and implementing locally tailored management strategies for wild birds in human‐modified landscapes by addressing their habitat selection, with regard to the balance between reducing human–wildlife conflicts and supporting biodiversity conservation in the context of global environmental change.

Decentralized Energy Swapping for Sustainable Wireless Sensor Networks Using Blockchain Technology

Wireless sensor networks deployed in energy-constrained environments face critical challenges relating to sustainability and protection. This paper introduces an innovative blockchain-powered safe energy-swapping protocol that enables sensor nodes to voluntarily and securely trade excess energy, optimizing usage and prolonging lifespan. Unlike traditional centralized management schemes, the proposed approach leverages blockchain technology to generate an open, immutable ledger for transactions, guaranteeing integrity, visibility, and resistance to manipulation. Employing smart contracts and a lightweight Proof-of-Stake consensus mechanism, computational and power costs are minimized, making it suitable for WSNs with limited assets. The system is built using NS-3 to simulate node behavior, energy usage, and network dynamics, while Python manages the blockchain architecture, cryptographic security, and trading algorithms. Sensor nodes checked their power levels and broadcast requests when energy fell under a predefined threshold. Neighboring nodes with surplus power responded with offers, and intelligent contracts facilitated secure exchanges recorded on the blockchain. The Proof-of-Stake-based consensus process ensured efficient and secure validation of transactions without the energy-intensive need for Proof-of-Work schemes. The simulation results indicated that the proposed approach reduces wastage and significantly boosts network resilience by allowing nodes to remain operational longer. A 20% increase in lifespan is observed compared to traditional methods while maintaining low communication overhead and ensuring secure, tamper-proof trading of energy. This solution provides a scalable, safe, and energy-efficient answer for next-generation WSNs, especially in applications like smart cities, precision agriculture, and environmental monitoring, where autonomy of energy is paramount.

Management strategy for building—photovoltaic with battery energy storage

Abstract Combining buildings with photovoltaic (PV) is very promising, whether a building-integrated photovoltaic (BIPV) or building-attached PV (BAPV) program. In this paper, we take a home building as an example to design a feasible energy management scheme; we classify the home loads into dispatchable and nondispatchable loads and optimize the operating hours of dispatchable loads to obtain lower electricity bills and higher PV consumption rates. We perform a detailed analysis of the proposed strategy and fully validate it, and the proposed plan has been proven to perform better.

Adaptive Handover Management in High-Mobility Networks for Smart Cities

The seamless handover of mobile devices is critical for maximizing the potential of smart city applications, which demand uninterrupted connectivity, ultra-low latency, and performance in diverse environments. Fifth-generation (5G) and beyond-5G networks offer advancements in massive connectivity and ultra-low latency by leveraging advanced technologies like millimeter wave, massive machine-type communication, non-orthogonal multiple access, and beam forming. However, challenges persist in ensuring smooth handovers in dense deployments, especially in higher frequency bands and with increased user mobility. This paper presents an adaptive handover management scheme that utilizes reinforcement learning to optimize handover decisions in dynamic environments. The system selects the best target cell from the available neighbor cell list by predicting key performance indicators, such as reference signal received power and the signal–interference–noise ratio, while considering the fixed time-to-trigger and hysteresis margin values. It dynamically adjusts handover thresholds by incorporating an offset based on real-time network conditions and user mobility patterns. This adaptive approach minimizes handover failures and the ping-pong effect. Compared to the baseline LIM2 model, the proposed system demonstrates a 15% improvement in handover success rate, a 3% improvement in user throughput, and an approximately 6 sec reduction in the latency at 200 km/h speed in high-mobility scenarios.

Spatial-situational approach to airport transport security management

The trend in the development of systems for ensuring and managing aviation security of transport facilities in recent years has acquired the character of a transition from classical regulatory management schemes to automated control schemes using procedures based on the theory of optimal control. A number of factors can be identified that reduce the effectiveness of security management in the current system: problems related to time, post-factum processing of situational events, non-systemic collection and processing of information, the problem of hypothetical and potential security threats, the problem of security integrality and security systems integrality, the problem of indivisibility of security and the problem of vulnerability of transport infrastructure and, finally, the problems of forecasting the development of negative events. All this implies a transition to information security management, which is based on a spatial-situational approach. The paper substantiates the emergence of threat space, protection space and security space and shows the possibilities of using these spaces to solve the problems of formalization of security management procedures in the modeling process.

Implementing a fishery improvement programme to manage the common cuttlefish (Sepia officinalis) in artisanal sea and lagoon fisheries: The case study of the Chioggia’s fleet

In the light of reducing the impact of fishery, artisanal fisheries hold great potential to achieve the sustainable use of marine resources if locally managed at sub-regional level (i.e., within the same province or fleet) and by implementing mitigation systems. The Chioggia small-scale fishing fleet represents a study case in an overexploited Mediterranean sub-region, operating both in the Venice Lagoon and the North Adriatic Sea. During the spawning period, this small-scale fishery targets the same target species, the common cuttlefish (Sepia officinalis), which, over the past thirty years, has shown a general decline in catch trends. Cuttlefish represent a high-value resource at all life stages, with both adults and juveniles considered targets of the artisanal fishery. Additionally, eggs are consistently laid on fishing gear during the breeding season and must be removed by fishers to prevent a reduction in fishing efficiency. These aspects contribute to the vulnerability of the common cuttlefish stocks, calling for a complementary management approach. We researched methods from the peer-reviewed literature, and adapted methods to reflect the environmental conditions of the sea and lagoon, and small-scale fishing methods. We combined into a complementary management approach: i) mitigation systems to reduce and collect eggs discarded during fishing operations, ii) semi-natural juvenile rearing diets to potentially release fishing pressure and support natural population, and iii) small-scale supply chain to both raise awareness about this resource vulnerability and promote the activity of fishers adopting virtuous behaviours. We tested these three functional management units in collaboration with lagoon and sea fishers and local stakeholders. We showed that the use of egg collectors, as an alternative spawning structure, performed well to limit the loss of the eggs laid upon the fishing gears. Second, we showed that Mixed and Natural diets contributed significantly to the growth rate of hatchlings compared to artificial diets. Finally, we demonstrated a shared interest in products derived from sustainable fisheries from the public, fishers and retailers. Therefore, the small-scale supply chain can represent a valid component to valorise the adoption of the whole management scheme. Overall, this complementary management approach can be adapted to and implemented in other local socio-economic communities of artisanal fishing in coastal environments worldwide. Complementary mitigation systems could work in synergy, overcoming the limitations of individual mitigation measures applied to diverse fishery resources.

DC‐link voltage stability enhancement in intermittent microgrids using coordinated reserve energy management strategy

AbstractIn recent years, due to its cost effectiveness and environmental advantages, demand for renewable energy resources has grown and their contributions to grid power has therefore increased while requiring effective frequency and voltage regulation. DC link voltage instability is a potential problem in solar energy microgrids, especially during an intermittency, where the system reliability degrades and DC link capacitor is under higher stress. In this article, a novel reserve energy management scheme based on battery and super capacitor storage is presented to stabilize the DC link voltage and reduce capacitor stress, while enhancing the system reliability. The scheme is tested in four different scenarios: Inverter connected DC‐microgrid with irradiance intermittencies, standalone DC‐microgrid without inverter and irradiance intermittencies, standalone DC‐microgrid without inverter and load intermittencies, and standalone DC‐microgrid with inverter under irradiance intermittencies. Simulation results indicate that the proposed control strategy stabilizes DC link voltage over all scenarios, even subject to large instances of irradiance or load changes. During low solar irradiance, the battery and super‐capacitor promote voltage stability by compensating power deficits from the utility grid in the inverter connected grid case. In stand alone mode, the battery provides power during intermittencies and the supercapacitor provides fast transient voltage compensation. The strategy is notable in reducing stress on DClink capacitors and mitigating inverter voltage fluctuations, ultimately enhancing inverter longevity. The results show that the proposed control scheme can improve voltage stability, mitigate the transient effects and guarantee the reliable operation of solar microgrids in variable conditions.

Charting water quality improvements and practice reversion with pesticide interventions at catchment scale.

Freshwater quality, and the impacts of farming practice on drinking water supplies, are of concern in many countries and time-limited catchment management interventions are commonly used to improve water quality. However, ending such schemes may result in practice reversion. This study adopts an interdisciplinary approach combining evidence from water quality monitoring data with a behavioural study of farmers to explore changes in land use practice with reference to the pesticide MCPA (2-methyl-4-chlorophenoxyacetic acid) following a catchment-based management scheme delivered in the cross-border Derg catchment in Northern Ireland/Ireland between 2018 and 2021. Analysis of over 10,000 water samples demonstrated that, compared to the Finn (Control), the scheme achieved a 15.2% and a 5.5% reduction in the frequency with which MCPA concentrations in the Derg (Treatment) exceeded the total (0.5μgL-1) and individual (0.1μgL-1) EU Drinking Water Directive limits for treated drinking water respectively. The post-intervention flow-weighted mean concentration (FWMC) of MCPA for Peak usage season (April-October) was 19% lower than pre-intervention in the Derg when compared to the Finn, although the during-intervention Peak season FWMC was lower in the Derg than post-intervention, suggesting practice reversion. The farmer survey and workshops provided further evidence of changes in pesticide usage, but also subsequent practice reversion due to a strong status quo bias for MCPA and other, mainly financial, barriers inhibiting a shift to the alternative pesticide, glyphosate. This study concludes that catchment approaches can be successful, but sustained investment in catchment measures is essential to effect meaningful long-term behavioural change.

A Versatile Converter and Consolidated Energy Management Scheme for Modern UAVs

A Versatile Converter and Consolidated Energy Management Scheme for Modern UAVs

Assessment of geological environment for the territorial scheme of municipal solid waste management

The current trends in the municipal waste management development are considered and the problems in using spatial geological data are shown, which consist in the complexity of combining geological information with other data in the waste management system. A methodological approach is proposed to take into account the geological environment specifics in the territorial scheme of waste management on the basis of digital mapping by the example of the Moscow region. An assessment zoning of a representative key site was carried out in the QGIS program according to its suitability for the municipal solid waste disposal depending on the presence of low-permeable soils and rocks in the geological section.

Development of a fault-tolerant management scheme for on demand real time data centre cloud environment

Fault tolerance in cloud data centers is a critical mechanism for handling the escalating frequency of failures. As the size and complexity of large-scale systems grow, the challenge of predicting and mitigating failures becomes increasingly exponential, rendering previous solutions inadequate for meeting the high-performance demands of both cloud users and providers. This paper aims to address the growing need for improved fault tolerance by developing a management computational intelligence scheme tailored for real-time, on-demand cloud data center environments. In this study, a fault-tolerant computational intelligence scheme was elicited for the parameters necessary for the design. A computational system was also designed to determine league winners based on scheduling checkpoints. Also, the designed system was simulated using java programming language in CloudSim simulation toolkit (3.0.3) with a customized Cloud Analyst Graphic User Interface (GUI) on the Eclipse Integrated Development Environment (IDE) Luna release 4.4. The developed system (Checkpointed League Winner Algorithm) was compared with existing scheme such as Ant Colony Optimization (ACO), Genetic Algorithm (GA) and League Championship Algorithm (LCA) in real time. Checkpointed League Winner Algorithm was also evaluated to check the scheme's resistance to faults and the improvement percentage of the cloud data centres. The parameters used to evaluate the scheme are: failure to perform Ratio (FPR), Failure that causes a Delay in Performance (FDP), and the Rate at which Performance improves (RPI). The result indicates that when the whole average life of each scheme is considered, Checkpointed League Winner Algorithm (CPLWA) results in a 38.2%, 29.9%, and 20.5% improvement over ACO, GA, and LCA, respectively. The average makespan of the scheme indicates that the Checkpointed League Winner Algorithm exhibits a significant improvement, outperforming the ACO, GA, and LCA with 41%, 33%, and 23%, respectively; the response time of the scheme indicates that the Checkpointed League Winner Algorithm outperformed the ACO, GA, and LCA with 54.3%, 56.6%, and 30.2%, respectively; and the failure ratio of the scheme indicates that the Checkpointed League Winner Algorithm performs better than existing meta-heuristics methods (ACO, GA, and LCA) with a lower failure ratio. This improvement can be attributed to the iterative structure, the migration, and the checkpointing approaches employed in the scheme. This study developed a fault tolerance computational intelligence scheme for an on-demand real-time data centre cloud environment in which the Checkpointed League Winner Algorithm outperformed the existing scheme in terms of response time, average makepan and failure ratio. It is then suggested to explore the application of the Checkpointed League Winner Algorithm scheme to address resource management, provisioning, and virtual machine placement challenges within distributed systems.

Evolution of Street Food Management in Asian Metropolises

Metropolises around the world witness the social disputes over the use of public space, especially those concerning the existence of street food. This article aims to study the development of street food management in Asian metropolises in four countries, including Japan, Singapore, South Korea, and Taiwan, both in terms of policy and operations for lessons learned in spatial management and providing application guidelines to street management in Thai context. The research methods included collecting secondary data from related research documents, along with collecting primary data on the format of street food in the metropolis. The results showed that the development street food management can be divided into 3 stages, including the developing economy stage, the high economic growth stage, and the developed economy stage. In Japan, there were regulations for street management, which did not allow any trading activities on the street. In Singapore, street management relocated the activities into the Hawker Centre where it developed into a UNESCO World Intangible Heritage. In South Korea, there was a progressive formalization and lively street management scheme used to attract tourists. Just like in Taiwan, it was organized as an inclusive night market. The principle for street food management can be divided into 3 components, including registration and licensing, allocating designated space, and management tools. These lessons learned can be applied to Bangkok under the concept of inclusive street management that takes into account of inclusive management with the livelihoods of socially vulnerable groups, providing convenient walking and transportation space, preserving the street life and vibrant street food culture, and maintaining the legitimacy of the use of public space. This will create a balance between pedestrian users and street food vendors.

Understanding Greenhouse Tomato (Solanum lycopersicum L.) Growers’ Perceptions for Optimal Phthorimaea absoluta (Meyrick) Management—A Survey in Greece

The tomato (Solanum lycopersicum L.) leafminer, Phthorimaea absoluta (Meyrick) (Lepidoptera: Gelechiidae), is an extremely invasive pest and is threatening tomato production worldwide. Several strategies have been developed and implemented for managing P. absoluta. Effective pest control strategies based on integrated pest management (IPM) schemes include different cultural practices and techniques. This study seeks to (a) examine the perspectives, attitudes, and opinions of greenhouse tomato producers in Greece regarding different methods of P. absoluta management and (b) to determine whether the perceived damage caused by P. absoluta could be predicted by the implementation of various control management strategies. A questionnaire was employed to ascertain the views and beliefs of the participants. The questionnaire comprised five-point Likert scale questions. Principal component analysis (PCA) and binary logistic regression analysis were applied to examine the relationship between the reported perceived insect damage and the utilization of control techniques. The study findings indicate that greater adoption of alternative control methods and higher levels of adherence to preventive measures against P. absoluta are associated with a perception of reduced levels of damage. Conversely, individuals with a strong reliance on pesticides use are more likely to perceive a higher level of damage. Ultimately, as tomato growers are trying to deal with P. absoluta, more education and research on other alternatives could help the reduction of chemical use, promoting more environmentally friendly practices. The findings highlight integrated pest management over pesticides for sustainable tomato production. This can guide future research and extension efforts to develop tailored P. absoluta management approaches for Greek greenhouse growers and similar environments.

Fuel Cycle Performance of the Wielenga Innovation Static Salt Reactor

This work presents a detailed fuel cycle analysis of an innovative static molten salt fast reactor called Wielenga Innovation Static Salt Reactor (WISSR). The fuel salt is a mixture of 55 mol% NaCl and 45 mol% (U,TRU)Cl3, and the reactivity is controlled by moving a variable amount of liquid fuel pneumatically. The pneumatic transfer of fuel salt allows flexible fuel management. To flatten the power distribution, a simple out-in fuel management scheme was adopted by discharging burned fuel from the interior core region, moving fuel salts across the radial regions inward, and adding fresh fuel to the outermost region. The current design of WISSR features a burner design for efficiently burning transuranic nuclides (TRU) recovered from pressurized water reactor used nuclear fuels. Using a fresh fuel with 57.4 at.% TRU in heavy metals, an equilibrium cycle length of 102.5 days could be maintained with a refueling rate of 403 L/cycle. In an equilibrium cycle, the discharged fuel burnup could reach 19.6 at.%, with 25% of the charged TRU destroyed at a low TRU conversion ratio of 0.18. Detailed cycle-by-cycle analyses showed that major neutronics performance parameters converged to the equilibrium cycle values in about 30 cycles by employing enrichment zoning in the startup core in a way to approximate the equilibrium cycle core compositions. During the transition cycles, the prematurely discharged fuel salt was recycled into the core without chemical processing to improve resource utilization.

Solutions for Retrofitting Catenary-Powered Transportation Systems Toward Greater Electrification in Smart Cities

Catenary-powered networks are expected to play a pivotal role in urban energy transition, due to the larger deployment of electric public transport, in-motion-charging (IMC) vehicles, and catenary-backed electric vehicle chargers. However, there are technical challenges that must be overcome to ensure the successful utilization of existing networks without compromising vehicle performance or compliance with network standards. This paper aims to validate the use of battery energy storage systems (BESS) built from second-life batteries as a means of retrofitting catenary-powered traction networks. The objective is to increase the network robustness without creating a negative impact on its overall operational efficiency. Consequently, more electrification projects can be implemented using the same network infrastructure without substantial modifications. Furthermore, a power management scheme is presented which allows the voltage and current range allowed in the catenary network and the BESS maximum charging rate to be controlled from user-defined values. The proposed control scheme is adept at customizing the BESS size for the specific application under consideration. Validation is performed on a case study of the trolleybus system in Bologna, Italy.

Triangulation and Delphi method analysis of alternative management scheme for sustainable public-rented flats

Purpose Currently, public-rented flats in Jakarta Province are managed by the Management Unit of Public-Rented Flats (MUPRF), which uses the Regional Revenue and Expenditure Budget (RREB) as the source of its financing. However, several previous studies have suggested that the MUPRF change its institutional scheme, to be more independent and not rely on the RREB as its source of finance. The study aims to identify three variable groups, public-rented flats’ characteristics, alternative institutional and financial schemes and challenges in the change of institutional and financial schemes. Design/methodology/approach This is a qualitative research, where both triangulation and the Delphi method are used to enrich findings. Triangulation is used to collect data from more than one source, and the Delphi method is used to gather opinions from experts and reach a consensus on the variables identified in the triangulation process. Findings Based on the findings there are 11 variables of public-rented flats’ characteristics, three variables of alternative institutional and financial schemes and four variables of challenges in the change of institutional and financial scheme. Research limitations/implications Through the triangulation process, only two sources were used, sources from previous research and regulations. In the Delphi method process, experts were staff from the Department of Community Housing and Settlement of the DKI Jakarta Province. Originality/value This research will be used as the basis on developing a system dynamics on how the MUPRF works as a system to figure out whether it can be changed into the alternative scheme proposed, with all the characteristics and challenges identified.

Linking habitat and population viability analysis models to account for vegetation dynamics, habitat fragmentation, and social behavior of a metapopulation of Florida scrub-jays

Population dynamics and viability are driven by interactions among habitat and species biology. The Florida scrub-jay (Aphelocoma coerulescens) is a declining and Federally Threatened bird species that requires mid-succession habitat of partly open soil surface with mid-height vegetation. This habitat is created and sustained in a dynamic state of vegetation growth and periodic natural (e.g., fire) or managed (e.g., mechanical clearing) disturbances. Florida scrub-jays once occupied open oak scrub habitats across much of peninsular Florida but have been reduced to a few regional metapopulations and scattered isolated remnant populations. Many of these populations are undergoing continuing decline as open scrub is either converted to residential development or transitions into closed pine and oak forests due to fire suppression. Long-term field studies have shown that breeding and survival rates are determined by the quality of the scrub habitat, with the demography influenced by and in turn mediating the social structure. Prior Population Viability Analyses (PVA) that included dependencies of demographic rates on habitat and social structure indicated that the east coast Florida metapopulations were fragmented into remnant protected patches that were too small and isolated to support long-term persistence, even if the remaining habitat area and quality was sustained. Moreover, recent modeling of habitat transitions under various proposed management schemes, in conjunction with implementation of Adaptive Resource Management (ARM), projected that the proportion of optimal habitat will continue to decline. In this study, we integrated these habitat projections within the PVA and found that the Brevard County mainland metapopulation is projected to decline toward extinction unless habitat quality, extent, and connectivity can be improved. Land managers have recently implemented new innovative methods for restoring optimal scrub habitat, identifying potential improvements in habitat connectivity of nearby populations, and translocation methods to increase and reinforce the demographic and genetic integrity of local populations. Our linked habitat-population models project that the combination of such habitat and population management actions can stabilize the metapopulation and achieve long-term viability.

Parameterless Gene-pool Optimal Mixing Evolutionary Algorithms.

When it comes to solving optimization problems with evolutionary algorithms (EAs) in a reliable and scalable manner, detecting and exploiting linkage information, i.e., dependencies between variables, can be key. In this article, we present the latest version of, and propose substantial enhancements to, the Gene-pool Optimal Mixing Evoutionary Algorithm (GOMEA): an EA explicitly designed to estimate and exploit linkage information. We begin by performing a largescale search over several GOMEA design choices to understand what matters most and obtain a generally best-performing version of the algorithm. Next, we introduce a novel version of GOMEA, called CGOMEA, where linkage-based variation is further improved by filtering solution mating based on conditional dependencies. We compare our latest version of GOMEA, the newly introduced CGOMEA, and another contending linkage-aware EA, DSMGA-II, in an extensive experimental evaluation, involving a benchmark set of 9 black-box problems that can only be solved efficiently if their inherent dependency structure is unveiled and exploited. Finally, in an attempt to make EAs more usable and resilient to parameter choices, we investigate the performance of different automatic population management schemes for GOMEA and CGOMEA, de facto making the EAs parameterless. Our results show that GOMEA and CGOMEA significantly outperform the original GOMEA and DSMGA-II on most problems, setting a new state of the art for the field.