Linearly constrained global optimization via piecewise-linear approximation

AbstractThis paper considers the problem of optimizing a continuous nonlinear objective function subject to linear constraints via a piecewise-linear approximation. A systematic approach is proposed, which uses a lattice piecewise-linear model to approximate the nonlinear objective function on a simplicial partition and determines an approximately globally optimal solution by solving a set of standard linear programs. The new approach is applicable to any continuous objective function rather than to separable ones only and could be useful to treat more complex nonlinear problems. A numerical example is given to illustrate the practicability

Parallel navigation for 3-D autonomous vehicles

summary:In this paper, parallel navigation is proposed to track the target in three-dimensional space. Firstly, the polar kinematics models for the vehicle and the target are established. Secondly, parallel navigation is derived by using polar kinematics models. Thirdly, cell decomposition method is applied to implement obstacle avoidance. Fourthly, a brief study is given on the influence of uncertainties. Finally, simulations are conducted by MATLAB. Simulation results demonstrate the effectiveness of the parallel navigation

An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms

An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms

Distribution of multi-level B cell subsets in thymoma and thymoma-associated myasthenia gravis

B-cell subsets in peripheral blood (PB) and tumor microenvironment (TME) were evaluated to determine myasthenia gravis (MG) severity in patients with thymoma-associated MG (TMG) and the distribution of B cells in type B TMG. The distribution of mature B cells, including Bm1-Bm5, CD19+ and CD20+ B cells and non-switched (NSMBCs) and switched (SMBCs) memory B cells, were determined in 79 patients with thymoma or TMG. Quantitative relationships between the T and TMG groups and the TMG-low and TMG-high subgroups were determined. NSMBCs and SMBCs were compared in TME and PB. Type B thymoma was more likely to develop into MG, with types B2 and B3 being especially associated with MG worsening. The percentage of CD19+ B cells in PB gradually increased, whereas the percentage of CD20+ B cells and the CD19/CD20 ratio were not altered. The (Bm2 + Bm2')/(eBm5 + Bm5) index was significantly higher in the TMG-high than in thymoma group. The difference between SMBC/CD19+ and NSMBC/CD19+ B cell ratios was significantly lower in the thymoma than TMG group. NSMBCs assembled around tertiary lymphoid tissue in thymomas of patients with TMG. Few NSMBCs were observed in patients with thymoma alone, with these cells being diffusely distributed. MG severity in patients with TMG can be determined by measuring CD19+ B cells and Bm1-Bm5 in PB. The CD19/CD20 ratio is a marker of disease severity in TMG patients. Differences between NSMBCs and SMBCs in PB and TME of thymomas can synergistically determine MG severity in patients with TMG.</p

A Brain-Controlled Vehicle System Based on Steady State Visual Evoked Potentials

In this paper, we propose a human-vehicle cooperative driving system. The objectives of this research are twofold: (1) providing a feasible brain-controlled vehicle (BCV) mode; (2) providing a human-vehicle cooperative control mode. For the first aim, through a brain-computer interface (BCI), we can analyse the EEG signal and get the driving intentions of the driver. For the second aim, the human-vehicle cooperative control is manifested in the BCV combined with the obstacle detection assistance. Considering the potential dangers of driving a real motor vehicle in the outdoor, an obstacle detection module is essential in the human-vehicle cooperative driving system. Obstacle detection and emergency braking can ensure the safety of the driver and the vehicle during driving. EEG system based on steady-state visual evoked potential (SSVEP) is used in the BCI. Simulation and real vehicle driving experiment platform are designed to verify the feasibility of the proposed human-vehicle cooperative driving system. Five subjects participated in the simulation experiment and real the vehicle driving experiment. The outdoor experimental results show that the average accuracy of intention recognition is 90.68 ± 2.96% on the real vehicle platform. In this paper, we verified the feasibility of the SSVEP-based BCV mode and realised the human-vehicle cooperative driving system.Fil: Zhang, Zhao. Civil Aviation University Of China; ChinaFil: Han, Shuning. Universitat de Vic - Universitat Central de Catalunya ; EspañaFil: Yi, Huaihai. China University Of Geosciences; ChinaFil: Duan, Feng. Nankai University; ChinaFil: Kang, Fei. Maebashi Institute Of Technology; JapónFil: Sun, Zhe. Riken; JapónFil: Solé Casals, Jordi. Universitat de Vic - Universitat Central de Catalunya; España. Nankai University; China. University of Cambridge; Reino UnidoFil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; Argentina. Nankai University; Chin

Muon radiography experiments on the subway overburden structure detection

Muon radiography is an innovative and non-destructive technique for internal density structure imaging, based on measuring the attenuation of cosmic-ray muons after they penetrate the target. Due to the strong penetration ability of muons, the detection range of muon radiography can reach the order of hundreds of meters or even kilometers. Using a portable muon detector composed of plastic scintillators and silicon photomultipliers, we performed a short-duration(1h) flux scanning experiment of the overburden above the platform and tunnel of the Xiaoying West Road subway station under construction. With the observation direction facing up, the detector is placed on the north side of the track and moved eastward from the platform section inside the station to the tunnel section. The scanning length is 264m and a total of 21 locations are observed. By comparing the observed and predicted values of the muon survival ratio at different locations, the experiment accurately detects the jump in thickness at the interface of the platform section and tunnel section. Furthermore, unknown anomalies caused by random placed light brick piles and side passage mouth above the observation locations are detected and confirmed later. This experiment verifies the feasibility of using natural muons to quickly detect abnormal structures of the overburden of tunnel, and shows that muon radiography has broad application prospects in tunnel safety and other similar aspects.Comment: 30 pages, 10 figure