An Effective Metaheuristic for Multiple Traveling Repairman Problem with Distance Constraints

Multiple Traveling Repairman Problem with Distance Constraints (MTRPD) is an extension of the NP-hard Multiple Traveling Repairman Problem. In MTRPD, a fleet of identical vehicles is dispatched to serve a set of customers with the following constraints. First, each vehicle's travel distance is limited by a threshold. Second, each customer must be visited exactly once. Our goal is to find the visiting order that minimizes the sum of waiting times. To solve MTRPD we propose to combine the Insertion Heuristic (IH), Variable Neighborhood Search (VNS), and Tabu Search (TS) algorithms into an effective two-phase metaheuristic that includes a construction phase and an improvement phase. In the former phase, IH is used to create an initial solution. In the latter phase, we use VNS to generate various neighborhoods, while TS is employed to mainly prohibit from getting trapped into cycles. By doing so, our algorithm can support the search to escape local optima. In addition, we introduce a novel neighborhoods’ structure and a constant time operation which are efficient for calculating the cost of each neighboring solution. To show the efficiency of our proposed metaheuristic algorithm, we extensively experiment on benchmark instances. The results show that our algorithm can find the optimal solutions for all instances with up to 50 vertices in a fraction of seconds. Moreover, for instances from 60 to 80 vertices, almost all found solutions fall into the range of 0.9 %-1.1 % of the optimal solutions' lower bounds in a reasonable duration. For instances with a larger number of vertices, the algorithm reaches good-quality solutions fast. Moreover, in a comparison to the state-of-the-art metaheuristics, our proposed algorithm can find better solutions

Hybrid Variable Neighborhood Search for Solving School Bus-Driver Problem with Resource Constraints

The School Bus-Driver Problem with Resource Constraints (SBDP-RC) is an optimization problem with many practical applications. In the problem, the number of vehicles is prepared to pick a number of pupils, in which the total resource of all vehicles is less than a predefined value. The aim is to find a tour minimizing the sum of pupils’ waiting times. The problem is NP-hard in the general case. In many cases, reaching a feasible solution becomes an NP-hard problem. To solve the large-sized problem, a metaheuristic approach is a suitable approach. The first phase creates an initial solution by the construction heuristic based on Insertion Heuristic. After that, the post phase improves the solution by the General Variable Neighborhood Search (GVNS) with Random Neighborhood Search combined with Shaking Technique. The hybridization ensures the balance between exploitation and exploration. Therefore, the proposed algorithm can escape from local optimal solutions. The proposed metaheuristic algorithm is tested on a benchmark to show the efficiency of the algorithm. The results show that the algorithm receives good feasible solutions fast. Additionally, in many cases, better solutions can be found in comparison with the previous metaheuristic algorithms

Green Banking Development: A Case Study of Vietnam

Purpose: The objectives determine factors affecting green banking development in Vietnam. The authors proposed policy implications that contributed to the green banking development in Vietnam.   Theoretical framework: For long-term sustainable economic development, many countries worldwide have chosen to develop a green economy, including the theory of green banking.   Design/methodology/approach:  The research method of the paper is a combination of qualitative and quantitative research methods. Qualitative research was conducted with a group discussion technique, checked the scales used, and consulted with banking managers on the research issue, thereby building the scales included in the research model and setting up and completing the questionnaire. Quantitative research was carried out from January to February 2023. Processing data by statistical methods, analyzing EFA and CFA, using linear structural model analysis (SEM) to test the fit of models and hypotheses with SPSS 20.0 software and Amos.   Findings: The article showed that banking technology substantially impacts green banking development among eight factors.   Research, Practical & Social implications: The study has inherited and supplemented the scale in the model and a new set of scales used to evaluate the development of green banks, systematized, increased, and developed more basic theoretical issues about banking green.   Originality/value: The paper's originality and value help researchers, managers, and policymakers for Vietnamese commercial banks, in particular, and the banking industry, in general, to apply to contribute to the development of green banking and the green economy in the future

Policy Implications for Green Banking Development in Vietnam

Purpose:  The article studies the factors affecting the development of green banking in Vietnam. Based on the research results, the authors proposed policy implications that contribute to the development of green banking in Vietnam.   Theoretical framework: The article studies the factors affecting the development of green banking in Vietnam. Based on the research results, the authors proposed policy implications that contribute to the development of green banking in Vietnam.   Design/methodology/approach: To survey the level of understanding of bank managers on issues related to green banking, green banking development, and the level of knowledge of officers and employees about green banking development areas, The authors used qualitative and quantitative methods. Quantitative research was carried out from January to February 2023. The authors used structural equation model analysis to test the fit of models with SPSS 20.0 and Amos.   Findings: Quantitative and qualitative indicators have been introduced to measure the development of green banking and the economy. The factor of banking technology has the most substantial impact on the development of green banking and the economy. This is a new research paper finding in the context of the banking industry's digital transformation.   Research, Practical & Social implications: The study also shows that green banking development depends on financial capacity, supporting policies, legal framework, and state regulations. In addition, the study has included the factors of green banking development affecting the green economy from different approaches and analytical methods to evaluate.   Originality/value: Developing green banks not only brings profits but also helps banks increase their prestige, reputation, and value. In addition, the development of green banking associated with the green economy is not only a form but will become the core value of the bank, recognized and appreciated in the trend of integration and sustainable development

Influence of different cultivating and food sources on growth of earthworm, perionyx excavatus (PERR.)

Earthworm, Perionyx Excavatus, has been studied and the potential of this epigeic earthworm species for processing organic waste is well known. The substrate and feeding material were considered as effector of the growth, life cycle of earthworms. The current study carried on the evaluation of various cultivating and feeding materials that influenced on growth of earthworms, by calculating biomass, the total number of worms and relative growth rate. As the results, the cow manure fed in cultured and feeding materials showed the suitable in the growth of earthworm, with significant differences from other group which based on worm manure as the substrate and feeding materials. For further study, the adding component, including coir, straw and soil have to be studied to find out the better materials in earthworm cultivation

The impacts of lead recycling activities to human health and environment in Dong Mai craft village, Hung Yen, Vietnam

Lead (Pb) recycling activities in Dong Mai village, Chi Dao commune, Van Lam district, Hung Yen province have been taking place for more than 30 years. The development of recycling activities contributed to the improvement of the local economics. However, along with economic development, Dong Mai craft village is facing to serious pollution. Soil, air and water polluted by lead (Pb) caused food containing Pb at higher levels than allowed limit from 20 to 40 times. The pollution had the bad effect on human health in this village. The investigation results showed that 100 % of employee who participated on melting lead and 63.5 % of local children were poisoned by Pb. Besides, the local people got diseases relating to skin, eyes, etc. This situation requires the provincial authorities to find immediate solutions to reduce the impacts of Pb recycling activities to environment and human.Hoạt động tái chế chì của thôn Đông Mai, xã Chỉ Đạo, huyện Văn Lâm, tỉnh Hưng Yên đã diễn ra hơn 30 năm nay. Sự phát triển của nghề tái chế đã làm góp phần cải thiện kinh tế của địa phương. Tuy nhiên, cùng với sự phát triển kinh tế, làng nghề Đông Mai đã và đang đối mặt với ô nhiễm môi trường nghiêm trọng. Môi trường đất, nước không khí bị ô nhiễm bởi chì (Pb) dẫn đến thực phẩm nhiễm chì ở hàm lượng cao hơn mức cho phép từ 20- 40 lần. Sự ô nhiễm gây ra những ảnh hưởng xấu tới sức khỏe của người dân làng nghề. Kết quả điều tra cho thấy 100% công nhân tham gia nấu chì và 63.5% trẻ em địa phương bị nhiễm độc chì. Bên cạnh đó, người dân địa phương còn bị mắc của các loại bệnh ngoài da, bệnh về mắt, …. Tình trạng này đòi hỏi chính quyền địa phương phải tìm ra giải pháp khẩn cấp để giảm thiểu tác động của những hoạt động tái chế chì tới môi trường và con người

Leukotriene A4 Hydrolase Genotype and HIV Infection Influence Intracerebral Inflammation and Survival From Tuberculous Meningitis.

BACKGROUND: Tuberculous meningitis (TBM) is the most devastating form of tuberculosis, yet very little is known about the pathophysiology. We hypothesized that the genotype of leukotriene A4 hydrolase (encoded by LTA4H), which determines inflammatory eicosanoid expression, influences intracerebral inflammation, and predicts survival from TBM. METHODS: We characterized the pretreatment clinical and intracerebral inflammatory phenotype and 9-month survival of 764 adults with TBM. All were genotyped for single-nucleotide polymorphism rs17525495, and inflammatory phenotype was defined by cerebrospinal fluid (CSF) leukocyte and cytokine concentrations. RESULTS: LTA4H genotype predicted survival of human immunodeficiency virus (HIV)-uninfected patients, with TT-genotype patients significantly more likely to survive TBM than CC-genotype patients, according to Cox regression analysis (univariate P = .040 and multivariable P = .037). HIV-uninfected, TT-genotype patients had high CSF proinflammatory cytokine concentrations, with intermediate and lower concentrations in those with CT and CC genotypes. Increased CSF cytokine concentrations correlated with more-severe disease, but patients with low CSF leukocytes and cytokine concentrations were more likely to die from TBM. HIV infection independently predicted death due to TBM (hazard ratio, 3.94; 95% confidence interval, 2.79-5.56) and was associated with globally increased CSF cytokine concentrations, independent of LTA4H genotype. CONCLUSIONS: LTA4H genotype and HIV infection influence pretreatment inflammatory phenotype and survival from TBM. LTA4H genotype may predict adjunctive corticosteroid responsiveness in HIV-uninfected individuals

Clinical Outcomes of Patients With Drug-Resistant Tuberculous Meningitis Treated With an Intensified Antituberculosis Regimen.

Drug-resistant tuberculous meningitis (TBM) is difficult to diagnose and treat. Mortality is high and optimal treatment is unknown. We compared clinical outcomes of drug-resistant and -susceptible TBM treated with either standard or intensified antituberculosis treatment. We analyzed the influence of Mycobacterium tuberculosis drug resistance on the outcomes of patients with TBM enrolled into a randomized controlled trial comparing a standard, 9-month antituberculosis regimen (containing rifampicin 10 mg/kg/day) with an intensified regimen with higher-dose rifampicin (15 mg/kg/day) and levofloxacin (20 mg/kg/day) for the first 8 weeks. The primary endpoint of the trial was 9-month survival. In this subgroup analysis, resistance categories were predefined as multidrug resistant (MDR), isoniazid resistant, rifampicin susceptible (INH-R), and susceptible to rifampicin and isoniazid (INH-S + RIF-S). Outcome by resistance categories and response to intensified treatment were compared and estimated by Cox regression. Of 817 randomized patients, 322 had a known drug resistance profile. INH-R was found in 86 (26.7%) patients, MDR in 15 (4.7%) patients, rifampicin monoresistance in 1 patient (0.3%), and INH-S + RIF-S in 220 (68.3%) patients. Multivariable regression showed that MDR (hazard ratio [HR], 5.91 [95% confidence interval {CI}, 3.00-11.6]), P < .001), was an independent predictor of death. INH-R had a significant association with the combined outcome of new neurological events or death (HR, 1.58 [95% CI, 1.11-2.23]). Adjusted Cox regression, corrected for treatment adjustments, showed that intensified treatment was significantly associated with improved survival (HR, 0.34 [95% CI, .15-.76], P = .01) in INH-R TBM. Early intensified treatment improved survival in patients with INH-R TBM. Targeted regimens for drug-resistant TBM should be further explored