A genetic algorithm for the vehicle routing optimization problem of logistics park distribution

Abstract The Vehicle Routing Problem of Logistics park distribution (VRPLPD) is an extension of the vehicle routing problem, which deals with simultaneous distribution of goods to customers. With the increasing importance of logistics activities, it is of great theoretical and practical significance to determine efficient and effective vehicle routes for simultaneous delivery activities. The study attempts to propose a genetic algorithm approach to tackle this problem. Numerical example is presented with parameter settings in order to demonstrate the applicability and feasibility of the proposed approach. The simulation is carried out in Simulink package of MATLAB. It is shown that Genetic Algorithms are highly effective in optimizing vehicle routing problem

Mitigating effect of clopidogrel and systematic management on adverse events after interventional therapy for coronary heart disease

Purpose: To investigate the efficacy of clopidogrel combined with systemic management care in the prevention of adverse events in patients with coronary heart disease after interventional therapy.Methods: 100 patients undergoing interventional therapy after coronary heart disease admitted to Jinan Third People’s Hospital from April 2018 to April 2020 were assigned at a ratio of 1:1 either into control (low-molecular-weight heparin (LMWH) injection) or study groups randomly (clopidogrel plus system management care). Thrombin time, prothrombin time, fibrinogen, incidence of adverse events, NIHSS score and QLI score were determined for the two groups.Results: There thrombin time, prothrombin time and fibrinogen in the two groups were similar (p >0.05). The study group showed a significantly lower incidence of adverse events than the control group (p < 0.05). The treatment administered to the study group resulted in a higher QLI (quality of life) scores than those in the control group (p < 0.05). Remarkably lower National Institutes of Health Stroke Scale (NIHSS) score was reported in the study group versus control group (p < 0.05).Conclusion: Clopidogrel plus systemic management care might be a preferable therapeutic strategy for patients with coronary heart disease undergoing interventional therapy. It reduces the incidence of adverse events, significantly improves the quality of life of patients, and enhances neurological function. Thus, this therapeutic strategy has significant promise in the management of coronary heart disease

Agent-based artificial financial market with evolutionary algorithm

In traditional financial studies, existing approaches are unable to address increasingly complex problems. In this paper, an artificial financial market is proposed, in accordance with the adaptation market hypothesis, using artificial intelligence algorithms. This market includes three types of agents with different investments and risk preferences, representing the heterogeneity of traders. Genetic network programming is combined with a state-actionreward-state-action (SARSA)(k) algorithm for designing the market to reflect the adaptation of technical agents. A pricing mechanism is taken into consideration, based on the auction mechanism of the Chinese securities market. The characteristics of price time series are analyzed to determine whether excessive volatility exists in four different markets. Explanations are provided for the corresponding financial phenomena considering the hypotheses under the proposed novel artificial financial market

Dynamic changes and multi-dimensional evolution of portfolio optimization

Although there has been an increasing number of studies investigate portfolio optimization from different perspectives, few attempts could be found that focus on the development trend and hotspots of this research area. Therefore, it motivates us to comprehensively investigate the development of portfolio optimization research and give some deep insights into this knowledge domain. In this paper, some bibliometric methods are utilized to analyse the status quo and emerging trends of portfolio optimization research on various aspects such as authors, countries and journals. Besides, ‘theories’, ‘models’ and ‘algorithms’, especially heuristic algorithms are identified as the hotspots in the given periods. Furthermore, the evolutionary analysis tends to presents the dynamic changes of the cutting-edge concepts of this research area in the time dimension. It is found that more portfolio optimization studies were at an exploration stage from mean-variance analysis to consideration of multiple constraints. However, heuristic algorithms have become the driving force of portfolio optimization research in recent years. Multidisciplinary analyses and applications are also the main trends of portfolio optimization research. By analysing the dynamic changes and multi-dimensional evolution in recent decades, we contribute to presenting some deep insights of the portfolio optimization research directly, which assists researchers especially beginners to comprehensively learn this research field

Raman Characterizations of Red Blood Cells With β-Thalassemia Using Laser Tweezers Raman Spectroscopy

This study aimed to study the differences in Raman spectra of red blood cells (RBCs) among patients with β-thalassemia and controls using laser tweezers Raman spectroscopy (LTRS) system.A total of 33 patients with β-thalassemia major, 49 with β-thalassemia minor, and 65 controls were studied. Raman spectra of RBCs for each sample were recorded. Principal component analysis (PCA), one-way analysis of variance (ANOVA), and independent-sample t test were performed.The intensities of Raman spectra of β-thalassemia (major and minor) RBCs were lower than those of controls, especially at bands 1546, 1603, and 1619 cm. The intensity ratio of band 1546 cm to band 1448 cm demonstrated that there was a significant difference between the spectra of β-thalassemia major (mostly below 2.15) and those of controls. The spectra of controls could be well distinguished from those of β-thalassemia major using PCA. After normalization, the spectra of two different genotypes with β/β mutations mainly overlapped, while those with β/β mutations had lower intensity at bands 1546, 1603, and 1619 cm.The present study provided Raman characteristics of RBCs in patients with β-thalassemia major and supported the use of LTRS as a method for screening β-thalassemia major. The recognition rate for β-thalassemia minor needs to be further improved

Herbal Medicine Cordyceps sinensis

Moderate-to-severe asthma has a substantial impact on the health-related quality of life (HR-QOL) of the patients. Cordyceps sinensis is a traditional Chinese medicine that is evaluated clinically for the treatment of many diseases, such as chronic allograft nephropathy, diabetic kidney disease, and lung fibrosis. In order to investigate the effects of Cordyceps sinensis on patients with moderate-to-severe persistent asthma, 120 subjects were randomized to receive Corbin capsule containing Cordyceps sinensis for 3 months (treatment group, n=60), whereas the control group (n=60) did not receive treatment with Corbin capsule. Inhaled corticosteroid and as-needed β-agonists were used in the treatment of both groups. HR-QOL was measured with the Juniper’s Asthma Quality of Life Questionnaire (AQLQ). The incidence of asthma exacerbation, pulmonary function testing, and serum measurements of inflammatory mediators were also evaluated. The results showed that the treatment group indicated a significant increase in AQLQ scores and lung function compared with the control group. The expression levels of the inflammation markers IgE, ICAM-1, IL-4, and MMP-9 in the serum were decreased and IgG increased in the treatment group compared with the control group. Therefore, the conclusion was reached that a formulation of Cordyceps sinensis improved the HR-QOL, asthma symptoms, lung function, and inflammatory profile of the patients with moderate-to-severe asthma. This trial is registered with ChiCTR-IPC-16008730

Airlines Content Recommendations Based on Passengers\u27 Choice Using Bayesian Belief Networks

Faced with the increasingly fierce competition in the aviation market, the strategy of consumer choice has gained increasing significance in both academia and practice. As ever-increasing travel choices and growing consumer heterogeneity, how do airline companies satisfy passengers\u27 needs? With a vast amount of data, how do airline managers combine information to excavate the relationship between independent variables to gain insight about passengers\u27 choices and value system as well as determining best personalized contents to them? Using the real case of China Southern Airlines, this paper illustrates how Bayesian belief network (BBN) can enable airlines dynamically recommend relevant contents based on predicting passengers\u27 choice to optimize the loyalty. The findings of this study provide airline companies useful insights to better understand the passengers\u27 choices and develop effective strategies for growing customer relationship

Federated Learning for Energy-limited Wireless Networks: A Partial Model Aggregation Approach

The limited communication resources, e.g., bandwidth and energy, and data heterogeneity across devices are two of the main bottlenecks for federated learning (FL). To tackle these challenges, we first devise a novel FL framework with partial model aggregation (PMA), which only aggregates the lower layers of neural networks responsible for feature extraction while the upper layers corresponding to complex pattern recognition remain at devices for personalization. The proposed PMA-FL is able to address the data heterogeneity and reduce the transmitted information in wireless channels. We then obtain a convergence bound of the framework under a non-convex loss function setting. With the aid of this bound, we define a new objective function, named the scheduled data sample volume, to transfer the original inexplicit optimization problem into a tractable one for device scheduling, bandwidth allocation, computation and communication time division. Our analysis reveals that the optimal time division is achieved when the communication and computation parts of PMA-FL have the same power. We also develop a bisection method to solve the optimal bandwidth allocation policy and use the set expansion algorithm to address the optimal device scheduling. Compared with the state-of-the-art benchmarks, the proposed PMA-FL improves 2.72% and 11.6% accuracy on two typical heterogeneous datasets, i.e., MINIST and CIFAR-10, respectively. In addition, the proposed joint dynamic device scheduling and resource optimization approach achieve slightly higher accuracy than the considered benchmarks, but they provide a satisfactory energy and time reduction: 29% energy or 20% time reduction on the MNIST; and 25% energy or 12.5% time reduction on the CIFAR-10.Comment: 32pages, 7 figure