DPb-MOPSO: A Novel Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization Algorithm

Particle swarm optimization system based on the distributed architecture over multiple sub-swarms has shown its efficiency for static optimization and has not been studied to solve dynamic multi-objective problems (DMOPs). When solving DMOP, tracking the best solutions over time and ensuring good exploitation and exploration are the main challenging tasks. This study proposes a novel Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization (DPb-MOPSO) algorithm including two parallel optimization levels. At the first level, all solutions are managed in a single search space. When a dynamic change is successfully detected in the objective values, the Pareto ranking operator is used to enable a multiple sub-swarm’ subdivisions and processing which drives the second level of enhanced exploitation. A dynamic handling strategy based on random detectors is used to track the changes of the objective function due to time-varying parameters. A response strategy consisting in re-evaluate all unimproved solutions and replacing them with newly generated ones is also implemented. Inverted generational distance, mean inverted generational distance, and hypervolume difference metrics are used to assess the DPb-MOPSO performances. All quantitative results are analyzed using Friedman's analysis of variance while the Lyapunov theorem is used for stability analysis. Compared with several multi-objective evolutionary algorithms, the DPb-MOPSO is robust in solving 21 complex problems over a range of changes in both the Pareto optimal set and Pareto optimal front. For 13 UDF and ZJZ functions, DPb-MOPSO can solve 8/13 and 7/13 on IGD and HVD with moderate changes. For the 8 FDA and dMOP benchmarks, DPb-MOPSO was able to resolve 4/8 with severe change on MIGD, and 5/8 for moderate and slight changes. However, for the 3 kind of environmental changes, DPb-MOPSO assumes 4/8 of the solving function on IGD and HVD metrics.<br>

Strategic crisis response: managerial implications and direction for recovery and survival

Purpose The purpose of this paper is to provide managers with insights to help survive a crisis, create advantage during slow-growth recoveries and thrive when the crisis is over. Given the environment at the time of this paper, this paper focuses on widespread crises, such as a public health crisis like COVID-19. Design/methodology/approach The authors offer a conceptual framework, grounded in the attribution theory and situation crisis communication theory (SCCT), for managers to use when determining which crisis response strategy is most appropriate to use during a crisis. Propositions based on this framework are provided. This paper focuses on widespread crises, such as a public health crisis, particularly on the COVID-19 pandemic. Based on the framework proposed for organizational crisis response strategy and recovery, several insights for managers across a variety of industries emerge. Consideration of the best strategic approach to a crisis is essential, and time is critical. This framework provides a starting point for creating a proper response strategy when a crisis arises that is not within the organization’s crisis management planning. Managerial implications for several industries, such as restaurant, hotel, airline, education, retail, medical and other professional services, and theoretical implications to further the advancement of understanding are provided. Findings The findings of this paper demonstrate that organizations that apply an accommodative strategy during unintentional crises will survive, while during intentional crises, they will thrive in the marketplace. Similarly, organizations that apply an offensive strategy during unintentional crises will thrive, while during intentional crises, they will survive in the marketplace. Practical implications This paper provides a framework highlighting strategies that best protect an organization during both internally and externally caused crises. The response strategy and crisis framework are based on the attribution theory and SCCT. Building on this framework, six propositions are postulated. In keeping with this strategy and crisis framework, this study provides several crisis response insights for managers across a variety of industries. These suggestions act as a guide for managers when assessing how to respond in the early days of a crisis and what to do to recover from it. Originality/value This paper provides a crisis-strategy matrix, grounded in the attribution theory and SCCT, to provide decision-making guidance to help managers survive a crisis, create advantage during slow-growth recoveries and thrive when the crisis is over. The authors provide multiple industry insights related to the “how to” and the “what to” in the recovery from and survival through internally and externally caused crises.

Primary Frequency Stability Support of a DFIG in Association With Pitch Angle Control

For an electric power grid that has large penetration levels of variable renewable energy including wind generation and photovoltaics, the system frequency stability is jeopardized, which is manifest in lowering frequency nadir and settling frequency. This paper suggests an enhanced primary frequency response strategy of a doubly-fed induction generator (DFIG) in association with pitch angle control. The DFIG works in de-loaded operation with a certain reserve power via pitch angle control prior to disturbances for frequency regulation. To address this, a function of the pitch angle is employed that decreases the pitch angle with time to slowly feed the active power to the power gird. The simulation results demonstrate the effectiveness and feasibility of the proposed primary frequency response strategy including the settling frequency and frequency nadir.

Maternal Mental Health under COVID-19 Pandemic in Thailand

Numerous nations have implemented lockdown measures in response to the COVID-19 pandemic. As a consequence of the lockdown on daily living, social participation, and health service accessibility, vulnerable people, for example, new mothers, may experience an increase in mental health problems. This cross-sectional survey was conducted to investigate the impact of the COVID-19 pandemic lockdown on Thai new mothers and the variables affecting their mental health. The survey data were collected from 903 Thai mothers with infants aged 0–12 months using an online platform and a face-to-face interview questionnaire survey between 17 July and 17 October 2020, during the first nationwide COVID-19 lockdown period. For the final analysis, there were 862 participants who completed all of the questions. The full exploratory analysis was performed by multivariable linear regression to identify the variables influencing maternal mental health. Our study demonstrated that new mothers reported feeling a high extent to some extent of worry (44.9%), increased appetite (40.4%), becoming easily annoyed or irritable (39.1%), and feeling down (33.5%), whereas 82.7% felt able to cope with the first lockdown situation. Practiced relaxation techniques were associated with positive maternal mental health (adjusted β = 1.05, 95% CI 0.57 to 1.52, p < 0.001). The perceived impact of the COVID-19 lockdown was on the household’s ability to pay for rent, to make mortgage payments (adjusted β = −1.59, 95% CI −2.87 to −0.36, p = 0.011), the household’s ability to pay for other essentials, such as utilities and medication (adjusted β = −1.99, 95% CI −3.16 to −0.81, p = 0.001), household crowding after lockdown (adjusted β = −3.46, 95% CI −4.86 to −2.06, p < 0.001), and not going outside or doing outdoor activities (adjusted β = −2.22, 95% CI −3.35 to −1.08, p < 0.001). These impacts were significantly associated with negative mental health. In conclusion, our results emphasize the critical need for continuous monitoring of maternal mental health and developing an effective response strategy and activity for promoting maternal mental health under the stress of repetitive lockdowns and increased economic pressures.

Evaluation of Epidemiological Investigation 1 -2-5 Implementation Program in Sukabumi

Epidemiological investigations as part of the malaria surveillance system in Indonesia are carried out through the 1-2-5 method. Assessing the 1-2-5 strategy compliance level at the district level is the first step towards determining whether the surveillance and response strategy is working as planned or not. This study was conducted in order to determine whether PE 1-2-5 had been implemented in health centers (puskesmas) in malaria receptive areas according to the technical guidelines issued by the Indonesian Ministry of Health. Health centers were determined through purposive sampling technique. The sampling is determined by selecting health centers that have been doing malaria vector control service in 2018 and 2019. Ten Puskesmas in malaria receptive areas in Sukabumi District were selected. The informants in this study were the key players in the malaria program at the health centers: the head of the health centers, the manager of the malaria program, and the village malaria officer (JMD) who were involved in the vector control process in 2018 and 2019 at the selected health centers. Data collection was conducted through in-depth interviews done by researcher with informants. The interview showed that the malaria program personnel in Sukabumi are doing the strategy as best as possible in order to achieve malaria elimination. 1-2-5 surveillance program in Sukabumi district has been implemented even though the implementation is not as ideal as the technical guidelines suggested by the Indonesian Ministry of Health, Sukabumi district still applied the strategy based on it by adjusting various aspects (resource situation and the availability of facilities) to the suitable condition in Sukabumi.

Cortical and thalamic influences on striatal involvement in instructed, serial reversal learning; implications for the organisation of flexible behaviour.

Cognitive flexibility is essential for enabling an individual to respond adaptively to changes in their environment. Evidence from human and animal research suggests that the control of cognitive flexibility is dependent on an array of neural architecture. Cortico-basal ganglia circuits have long been implicated in cognitive flexibility. In particular, the role of the striatum is pivotal, acting as an integrative hub for inputs from the prefrontal cortex and thalamus, and modulation by dopamine and acetylcholine. Striatal cholinergic modulation has been implicated in the flexible control of behaviour, driven by input from the centromedian-parafascicular nuclei of the thalamus. However, the role of this system in humans is not clearly defined as much of the current literature is based on animal work. Here, we aim to investigate the roles corticostriatal and thalamostriatal connectivity in serial reversal learning. Functional connectivity between the left centromedian-parafascicular nuclei and the associative dorsal striatum was significantly increased for negative feedback compared to positive feedback. Similar differences in functional connectivity were observed for the right lateral orbitofrontal cortex, but these were localised to when participants switched to using an alternate response strategy following reversal. These findings suggest that connectivity between the centromedian-parafascicular nuclei and the striatum may be used to generally identify potential changes in context based on negative outcomes, and the effect of this signal on striatal output may be influenced by connectivity between the lateral orbitofrontal cortex and the striatum.

DPb-MOPSO: A Novel Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization Algorithm

Particle swarm optimization system based on the distributed architecture has shown its efficiency for static optimization and has not been studied to solve dynamic multiobjective problems (DMOPs). When solving DMOP, tracking the best solutions over time and ensuring good exploitation and exploration are the main challenging tasks. This study proposes a novel Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization (DPb-MOPSO) algorithm including two parallel optimization levels. At the first level, all solutions are managed in a single search space. When a dynamic change is successfully detected, the Pareto ranking operator is used to enable a multiswarm subdivisions and processing which drives the second level of enhanced exploitation. A dynamic handling strategy based on random detectors is used to track the changes of the objective function due to time-varying parameters. A response strategy consisting in re-evaluate all unimproved solutions and replacing them with newly generated ones is also implemented. Inverted generational distance, mean inverted generational distance, and hypervolume difference metrics are used to assess the DPb-MOPSO performances. All quantitative results are analyzed using Friedman's analysis while the Lyapunov theorem is used for stability analysis. Compared with several multi-objective evolutionary algorithms, the DPb-MOPSO is robust in solving 21 complex problems over a range of changes in both the Pareto optimal set and Pareto optimal front. For 13 UDF and ZJZ functions, DPb-MOPSO can solve 8/13 and 7/13 on IGD and HVD with moderate changes. For the 8 FDA and dMOP benchmarks, DPb-MOPSO was able to resolve 4/8 with severe change on MIGD, and 5/8 for moderate and slight changes. However, for the 3 kind of environmental changes, DPb-MOPSO assumes 4/8 of the solving function on IGD and HVD. <br>