scholarly journals A Novel Multi-Population Based Chaotic JAYA Algorithm with Application in Solving Economic Load Dispatch Problems

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1946 ◽  
Author(s):  
Jiangtao Yu ◽  
Chang-Hwan Kim ◽  
Abdul Wadood ◽  
Tahir Khurshiad ◽  
Sang-Bong Rhee
Keyword(s):  
Total Population ◽  
Population Based ◽  
Economic Load Dispatch ◽  
Jaya Algorithm ◽  
Ramp Rate ◽  
Promising Alternative ◽  
Capacity Limits ◽  
Alternative Approach ◽  
Global Optima ◽  
Ramp Rate Limits

The economic load dispatch (ELD) problem is an optimization problem of minimizing the total fuel cost of generators while satisfying power balance constraints, operating capacity limits, ramp-rate limits and prohibited operating zones. In this paper, a novel multi-population based chaotic JAYA algorithm (MP-CJAYA) is proposed to solve the ELD problem by applying the multi-population method (MP) and chaotic optimization algorithm (COA) on the original JAYA algorithm to guarantee the best solution of the problem. MP-CJAYA is a modified version where the total population is divided into a certain number of sub-populations to control the exploration and exploitation rates, at the same time a chaos perturbation is implemented on each sub-population during every iteration to keep on searching for the global optima. The proposed MP-CJAYA has been adopted to ELD cases and the results obtained have been compared with other well-known algorithms reported in the literature. The comparisons have indicated that MP-CJAYA outperforms all the other algorithms, achieving the best performance in all the cases, which indicates that MP-CJAYA is a promising alternative approach for solving ELD problems.

Evolutionary Algorithms for Economic Load Dispatch Having Multiple Types of Cost Functions

2016 ◽  
pp. 201-226
Author(s):  
Provas Kumar Roy ◽  
Moumita Pradhan ◽  
Tandra Pal
Keyword(s):  
Evolutionary Algorithms ◽  
Optimization Methods ◽  
Population Based ◽  
Optimization Techniques ◽  
Economic Load Dispatch ◽  
Thermal Systems ◽  
Generation Scheduling ◽  
Valve Point Effect ◽  
Real Coded Genetic Algorithm ◽  
Ramp Rate Limits

This chapter presents various novel evolutionary algorithms, namely Real Coded Genetic Algorithm (RGA), two variants of Biogeography-Based Optimization (BBO), and three variants of Particle Swarm Optimization (PSO) in order to find the optimal power generation scheduling to simultaneously optimize fuel cost and power loss for solving constrained economic load dispatch problems of all thermal systems, considering multiple fuel operation and valve point effect. The effectiveness of the proposed algorithms is demonstrated in five different ELD problems, considering different constraints such as transmission losses, ramp rate limits, multi-fuel options and valve point loading. Comparative studies are carried out to examine the effectiveness and superiority of the proposed approaches. A comparison of simulation results reveals optimization usefulness of the proposed BBO scheme over other well established population based optimization techniques. It is also found that the convergence characteristics of the BBO algorithm are better than other optimization methods.

scholarly journals SARS-CoV-2 infection is at herd immunity in the majority segment of the population of Qatar

2021 ◽  
Author(s):  
Mohamed H Al-Thani ◽  
Elmoubasher Farag ◽  
Roberto Bertollini ◽  
Hamad Eid Al Romaihi ◽  
Sami Abdeen ◽  
...  
Keyword(s):  
Total Population ◽  
Herd Immunity ◽  
Geographic Location ◽  
Population Based ◽  
Infection Prevalence ◽  
Cross Sectional ◽  
Previous Infection ◽  
Current Infection ◽  
Polymerase Chain ◽  
Population Based Survey

Abstract Background Qatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess ever and/or current infection prevalence in this population. Methods A cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and current infection positivity through polymerase chain reaction (PCR) testing. Associations with antibody and PCR positivity were identified through regression analyses. Results Study included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, and previous infection diagnosis. PCR positivity was 11.3% (95% CI: 9.9-12.8%) and was significantly associated with nationality, geographic location, occupation, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was 60.6% (95% CI: 58.6-62.5%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical—an infection severity rate of 0.5% (95% CI: 0.2-1.0%). Conclusions Six in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or mild infections.

scholarly journals Psychotropic and pain medication use in individuals with traumatic brain injury—a Swedish total population cohort study of 240 000 persons

2021 ◽  
Vol 92 (5) ◽  
pp. 519-527
Author(s):  
Yasmina Molero ◽  
David James Sharp ◽  
Brian Matthew D'Onofrio ◽  
Henrik Larsson ◽  
Seena Fazel
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Total Population ◽  
Medication Use ◽  
Population Based ◽  
Pain Medication ◽  
Short Term ◽  
Pain Medications ◽  
Before And After

ObjectiveTo examine psychotropic and pain medication use in a population-based cohort of individuals with traumatic brain injury (TBI), and compare them with controls from similar backgrounds.MethodsWe assessed Swedish nationwide registers to include all individuals diagnosed with incident TBI between 2006 and 2012 in hospitals or specialist outpatient care. Full siblings never diagnosed with TBI acted as controls. We examined dispensed prescriptions for psychotropic and pain medications for the 12 months before and after the TBI.ResultsWe identified 239 425 individuals with incident TBI, and 199 658 unaffected sibling controls. In the TBI cohort, 36.6% had collected at least one prescription for a psychotropic or pain medication in the 12 months before the TBI. In the 12 months after, medication use increased to 45.0%, an absolute rate increase of 8.4% (p<0.001). The largest post-TBI increases were found for opioids (from 16.3% to 21.6%, p<0.001), and non-opioid pain medications (from 20.3% to 26.6%, p<0.001). The majority of prescriptions were short-term; 20.6% of those prescribed opioids and 37.3% of those with benzodiazepines collected prescriptions for more than 6 months. Increased odds of any psychotropic or pain medication were associated with individuals before (OR: 1.62, 95% CI: 1.59 to 1.65), and after the TBI (OR: 2.30, 95% CI: 2.26 to 2.34) as compared with sibling controls, and ORs were consistently increased for all medication classes.ConclusionHigh rates of psychotropic and pain medications after a TBI suggest that medical follow-up should be routine and review medication use.

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