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In this article, an Improved Particle Swarm Optimization (IPSO) is proposed for solving global optimization and hyperparameter optimization. This improvement is proposed to reduce the probability of particles falling into local optimum and alleviate premature convergence and the imbalance between the exploitation and exploration of the Particle Swarm Optimization (PSO). The IPSO benefits from a new search policy named group-based update policy. The initial population of IPSO is grouped by the k-means to form a multisubpopulation, which increases the intragroup learning mechanism of particles and effectively enhances the balance between the exploitation and exploration. The performance of IPSO is evaluated on six representative test functions and one engineering problem. In all experiments, IPSO is compared with PSO and one other state-of-the-art metaheuristics. The results are also analyzed qualitatively and quantitatively. The experimental results show that IPSO is very competitive and often better than other algorithms in the experiments. The results of IPSO on the hyperparameter optimization problem demonstrate its efficiency and robustness. [ABSTRACT FROM AUTHOR]

This paper introduces a new metaheuristic algorithm called bacteria phototaxis optimizer (BPO). It is designed to solving optimization issues. Inspired by the bacteria phototaxis under the control of photosensory proteins in nature, and based on the basic law of bacterial colony growth and evolution, we have designed the photosensory protein concentration, phototaxis motion and growth operators. These three operators exhibit a highly adaptive and information interaction mechanism. The goal is to simulate the phototaxis process of bacteria and form a complete model of BPO. At the same time, BPO is compared with eight most representative as well as newly generated metaheuristics. Its performance is verified by using 23 well-known benchmark functions with three different types. Additionally, we have conducted several evaluation processes, such as qualitative and quantitative analysis as well as parametric and nonparametric tests. Finally, five classical engineering design problems are used to further test the effectiveness of the algorithm in solving constrained problems. The aforementioned experimental results show that compared with other algorithms, BPO has better accuracy, convergence, and robustness and shows strong competitiveness and optimization performance. [ABSTRACT FROM AUTHOR]

Background: Although the role of staging laparoscopy (SL) in detecting radiologically occult M1 disease has been widely recognized, it is seldom used in China and its clinical value based on Chinese population has been rarely reported. The aim of this study is to identify the yield of SL for Chinese patients with advanced gastric cancer (AGC) and determine the proportions of patients in whom treatment plan is altered.Materials and Methods: The clinical data were retrospectively collected from 879 AGC patients who underwent SL without any definite signs of disseminated disease on imaging examination. The primary outcomes were the proportions of patients whose laparoscopy identified incurable factors (including M1 diseases and unresectable T4b diseases), and who had their treatment plan altered.Results: SL revealed incurable factors in 130 (14.8%) patients, including macroscopic peritoneal metastasis (n = 92), positive peritoneal cytology (n = 10), liver metastasis (n = 12), para-aortic lymph node metastasis (n = 1), and unresectable T4b tumor (n = 18). After SL, treatment plans were altered in 123 (14.0%) patients, among which 82 (63.1%) patients were not offered any further procedure and referred for chemotherapy. Among 749 M0 patients who immediately proceeded to radical gastrectomy after SL, new incurable factors were found at subsequent operations in 21 (2.8%) patients. Multivariate analysis showed that tumor size ≥8 cm, Borrmann type III and IV, and tumor invasion of T4a and T4b in preoperative imaging examination were the predictive factors for peritoneal metastasis.Conclusions: SL detects additional incurable factors in Chinese AGC patients with potentially resectable disease and optimizes their treatments. A systematic and painstaking inspection of the whole abdominal cavity, including routine entry into the bursa omentalis, is necessary for improving the yield of SL. [ABSTRACT FROM AUTHOR]