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Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the research and practice of multi-agent systems, formation path planning is particularly crucial, as it not only ensures the safe operation of agents but also enhances the efficiency of the system in task execution. This study introduces a multi-agent formation path planning method adapted for dynamic and complex environments, ensuring the system’s real-time responsiveness in dynamic obstacle avoidance and formation shape maintenance. This paper develops two core algorithms： One is dedicated to local motion planning and the other is focused on global path planning. The local motion planning algorithm iteratively uses semidefinite programming and quadratic programming to identify obstacle-free convex regions around agents and optimizes formation parameters through continuous convex optimization techniques. This approach effectively addresses the issue of multi-agent formation avoiding dynamic obstacles, ensuring the stability of the formation while adhering to environmental constraints. In the global path planning phase, this concept is further utilized by sampling obstacle-free convex regions in free space, combined with constraint optimization to calculate transitional formations between the initial and target formations, and employing graph search algorithms to find the optimal path to the target formation. This paper utilizes MATLAB to build a complex warehouse environment with both dynamic and static obstacles to verify the effectiveness of the method. It also compares the approach with the virtual structure method and probabilistic roadmap (PRM), demonstrating its superiority in terms of efficiency and accuracy. [ABSTRACT FROM AUTHOR]

To solve the constrained optimization problem, a new algorithm WDFSO is obtained by combining the exterior penalty function method and an improved snake optimization algorithm. Firstly, the constrained optimization problem is transformed into a series of bound-constrained optimization problems by the exterior penalty function method. Then, the improved snake optimization algorithm based on the oppositional learning of the centroid variation strategy and the population classification strategy is used to solve the bound-constrained optimization problem, and obtain the solution of the constrained optimization problem. In order to verify the effectiveness of WDFSO algorithm, 19 benchmark constrained optimization problems in CEC2006 are selected for numerical experiments, and the Wilcoxon rank sum test is used to prove the algorithm significance. The experimental results show that WDFSO algorithm has higher convergence accuracy and better stability than the comparison algorithms. Finally, WDFSO algorithm is applied to solve two engineering constraint optimization problems, and the results show that WDFSO algorithm has better performance. [ABSTRACT FROM AUTHOR]

To address the poor tracking accuracy, the high probability of sideslip and instability of intelligent vehicles in extreme working conditions with high speed and low adhesion, this paper proposes a layered control architecture trajectory tracking algorithm for distributed electric drive intelligent vehicles. Firstly, a Linear Time-Varying Model Predictive Control (LTVMPC) with varying degrees of freedom is built on the three-degree-of-freedom monorail vehicle dynamics model. LTVMPC is employed to solve the constrained optimization problem by rolling to obtain the optimal front wheel angle. In the meantime, the desired torque output of the PID longitudinal driver model is empolyed to achieve vehicle speed tracking. Secondly, a lower direct yaw moment controller is designed through Linear Quadratic Regulator (LQR) and the calculated additional yaw moment is distributedbased on vertical load optimization distribution method. Finally, the co-simulation platform of Carsim and Matlab/Simulink is built, and the effectiveness of the trajectory tracking control is simulated and analyzed. It is shown the traj'ectory tracking control strategy significantly improves the trajectory tracking accuracy and lateral stability of distributed electric drive intelligent vehicles on both high-speed & high adhesion road surfaces and high-speed & low adhesion ones. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Dalian University of Technology / Dalian Ligong Daxue Xuebao is the property of Journal of Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rubber Industry is the property of Editorial Office of China Rubber Industry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bayesian method is commonly used in the reliability assessment of repairable systems with small samples in fields such as aerospace.The knowledge about the informative prior and/or failure data from repairable systems may not be collected as precisely as possible due to uncertain factors,but can be obtained in terms of lower and upper bounds.For the case of such interval uncertainty information,the Bayesian reliability analysis method of multiple repairable whose failure process can follow the power law process(PLP)is studied in this paper.Under the informative priors,the interval-based Bayesian posterior analysis of the PLP is essentially transformed into solving the constrained optimization problem in which the objective function is just the traditional Bayesian posterior analysis result of the PLP under the informative priors.The feasibility and effectiveness of the proposed method is verified with specific enginee-ring examples.The results show that the proposed interval-based Bayesian method of the PLP can provide a refe-rence method for the reliability assessment of repairable systems with small samples in consideration of the influence of uncertain factors.

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Constrained multi-objective evolutionary algorithms (CMOEAs) can deal with multiple conflicting objective functions and constraints simultaneously and guide the population towards the optimal solution in the feasible domain, which has received extensive attention from researchers. This paper firstly introduces the relevant definitions of constrained multi-objective optimization problems (CMOPs) and three classifications of multi-objective evolutionary algorithms (MOEAs); secondly, it systematically analyzes the current constraint processing mechanisms in CMOEAs, and condenses the current four main constraint processing methods; Then, the research progress of CMOEAs is reviewed in detail from three aspects: dominance-based, index-based, and decomposition-based; finally, the challenges and future research directions of CMOEAs are pointed out. [ABSTRACT FROM AUTHOR]

Due to the overlap of time and space coverage between tasks in mobile crowd sensing, repeated data collection may happen and cause data redundancy problem. In view of this, this paper proposed a task allocation method to reduce data redundancy within and between tasks. Firstly, this method designed a trajectory sequence prediction model based on the long short-term memory (LSTM) neural network, to predict trajectory sequences of task participants within subdivided spatial-temporal units. Then based on the trajectory prediction results, the method proposed an optimization model to minimize data redundancy. Specifically, the optimization model constrained the data redundancy within a single task by minimizing the data redundancy metric in each spatial-temporal unit, and limited the data redundancy between multiple tasks by maximizing the reuse of the sensing data of each task participant in a spatial-temporal unit. Experimental results verify that the proposed task allocation method can effectively reduce the data redundancy within and between tasks. [ABSTRACT FROM AUTHOR]

In order to solve the problem that it is difficult to get out of the local optimum to achieve further optimization in large-scale dense Distributed Constraint Optimization Problems (DCOPs). This paper proposed a local parallel search framework (LPOS) for solving algorithms of DCOPs. In LPOS, the Agent searches all the value assignments of its local neighbors in parallel according to its current value assignment to further expand the search of solution space, so as to avoid the algorithm falling into local optimum prematurely. In order to ensure the convergence of the algorithm, this paper designed an adaptive equilibrium factor K to balance the exploration and exploitation ability of the DCOPs solving algorithms. At the theoretical analysis, it proved that the LPOS can expand the search of solution space and the K can achieve the balance. The experimental results demonstrate that the performance of the proposed LPOS is better than the-state-of-the-art algorithms in both low density and high density. Specifically, LPOS significantly superior to the competitors when solving high density DCOPs. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Operations Research Transactions / Yunchouxue Xuebao is the property of Editorial office of Operations Research Transactions and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Operations Research Transactions / Yunchouxue Xuebao is the property of Editorial office of Operations Research Transactions and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at solving the premature convergence of YYPO algorithm, this paper introduced SA strategy into the switch phase between P, and P2 in YYPO, and proposed a novel hybrid single-object optimization algorithms YYPO-SA ( including YYPO-SAl and YYPO-SA2). YYPO-SA inherited the lightweight characteristics of YYPO, and combined the YYPO' s excellent global search ability with the powerful local search performance of SA. It used the proposed 28 test functions in the single objective practical parameter algorithm competition in 2013 Evolutionary Computing Conference as the benchmark. It empirically studied the performance of YYPO-SA2, YYPO, A-YYPO, IYYPO, and 3 state of the art algorithms-GWO, WOA, and SCA based on experimental results. The experimental res ults show that YYPO-SA can perform more stable and achieve more accurate solutions. At the end, this paper also applied YYPO-SA to solve the spring design task. The experimental results show that YYPO-SA can also solve the constrained optimization task well. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Differential evolution is a global optimization algorithm based on greedy competition mechanism, which has the advantages of simple structure, less control parameters, higher reliability and convergence. Combining with the constraint-handling techniques, the constraint optimization problem can be efficiently solved. An adaptive differential evolution algorithm is proposed by using generalized opposition-based learning (GOBL-ACDE), in which the generalized opposition-based learning is used to generate initial population and executes the generation jumping. And the adaptive trade-off model is utilized to handle the constraints as the improved adaptive ranking mutation operator is adopted to generate new population. The experimental results show that the algorithm has better performance in accuracy and convergence speed comparing with CDE, DDE, A-DDE and. And the effect of the generalized opposition-based learning and improved adaptive ranking mutation operator of the GOBL-ACDE have been analyzed and evaluated as well.

In order to solve the dynamic emission economic dispatch (DEED) problem with high-dimensional and large scale constraints, this paper proposed an adaptive multiobjective differential evolutionary algorithm (ADEA). The ADEA designed an adaptive differential crossover module, developed an improving current to best 1 crossover scheme to enhance the diversity of population. These strategies improved the exploration and exploitation ability of the ADEA, it also applied a repair strategy to deal with the equality and inequality constrains in DEED problem. Numerical experiments tested the effectiveness of ADEA on 10-unit system, and compared with several peer algorithms. Simulation results indicate that ADEA has good convergence. The uniformity and ductility of the Pareto front obtained by ADEA is better than that of the compared algorithms. It provides a more efficient scheduling decision-making method for power system dispatcher by a fuzzy decision method. [ABSTRACT FROM AUTHOR]

For the optimization of anti-jamming agile waveform for helicopter borne fire control radar, an agile phase coding waveform suitable for multi-pulse and short code length is designed based on singular value decomposition (SVD) and cyclic algorithm. First, we construct the constrained quadric optimization problem with low sidelobe ambiguity function in the target region. Second, the quartic is transformed into the quadric according to SVD decomposition, and an iterative convergence algorithm is designed. Third, a quadric iterative convergence algorithm is deduced based on the cyclic algorithm. Finally, the simulation results show that the two algorithms are close to each other in the design of agile waveform optimization performance, but the SVD decomposition algorithm has faster convergence speed, and the cycle calculation algorithm has higher operation speed. [ABSTRACT FROM AUTHOR]

Internet as an important carrier connected cloud and edge distributed in different areas, its best-effort service mode will cause problems such as fast consumption of network resources and path competition when supporting group control commands transfer. First, this paper transformed group control command transfer problem into constrained multi-Steiner trees with disjoint problem, and proposed a kind of improved genetic algorithm. The algorithm focused on improving the global search ability and alleviating the path competition. The experiment verifies by transfer success rate, convergence delay rate and solutions error rate shows that the algorithm is suitable for group command transfer between edge and cloud. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Priori geomagnetic information is important to the geomagnetic navigation. However in practice, the precision of the geomagnetic information is a greatly constraint to the development of the geomagnetic navigation. In order to solve this problem, this paper present a geomagnetic gradient bionic navigation method based on parallel approach without any priori information. Inspired by the evidence that many creatures can navigate using the Earth magnetic field, the navigation process can be considered as a convergence of multi-objective problem, and develop the bionics navigation model. By introducing the parallel approach method to the navigation process, the heading angle can be estimated with the information of magnetic field gradient. The simulation results show the proposed method is able to navigation effectively without magnetic priori information, just rely on the actual geomagnetic measurement, which has implies potential application in the future.

MapReduce model is a typical distributed computing model, which is widely used in large-scale data processing, and its performance depends largely on the data distribution status. As the data content is often unbalanced, coupled with the storage of randomness, so MapReduce model prone to data skew problem in the calculation process. In order to solve this problem, this paper establishes a data histogram for the data block and the whole file through the improved parallel histogram parallelization algorithm based on MapReduce. According to the data block distribution, we can judge the data skew degree of each storage nodes and define the file equilibrium deviation value as the measure of data skew, and then the data balance algorithm is used to reduce the file equilibrium deviation value. The improved MapReduce-based data histogram parallel construction algorithm can adapt to various types of data application scenarios. In the process of building the histogram, the Map side only needs to transmit histogram statistics to the Reduce side without transmitting the contents of the file. The data transfer can be almost negligible. The data balance algorithm based on histogram employs greedy strategy, which can obtain a better approximate solution of the optimal solution of equilibrium distribution. After several experiments, compared with the random block distribution algorithm, the improved algorithm reduce about 40% of the file balance deviation value and achieves a better data balance performance.

A multi-echelon inventory allocation technique with maintenance ratio for civil aircraft spare parts was proposed in this paper. Multi-echelon inventory allocation model was established, which integrates maintenance rate into METRIC (Multi-echelon technique for recoverable item control) model, and then marginal analysis method was applied to solve this model and accomplish multi-echelon inventory allocation of spare parts. Firstly, the theory of multi-echelon inventory allocation model with maintenance ratio was elaborated, and the mathematical model was established with the fleet availability as the optimization objective, the cost and the safeguard probability as the constraints. Secondly, the procedure of solving multi-echelon inventory allocation model considering the influence of maintenance ratio is discussed based on the marginal analysis method. Thirdly, landing gear LRU (Line repairable units) of a typical civil aircraft were selected as the research object, multi-echelon inventory allocation was investigated by considering maintenance ratio. The analysis results show that the minimum safeguard cost and fleet availability are respectively 2759833 dollars and 0.9806, and the number of LRU of multi echelon inventory allocation are obtained under the condition of satisfying the constrained optimization. The feasibility and effectiveness of the developed method are verified by comparing the traditional analysis method. This paper provides guidance for the accurate allocation of multi echelon inventory optimization for maintenance resources on the premise of reasonable cost reduction.

To solve the problem that how to design a big magnetic moment, small size, light weight, low power consumption magnetorquer with air core under the constraint of limited volume and power in CubSate, multiobjective optimization design method is used. Firstly, based on the structure of the square support with multiple layer of the enameled wire wrapped, the magnetic moment model, power consumption model and mass model are deduced from square support size, enameled wire diameter and turn number, respectively. Secondly, according to the model of magnetic moment and power consumption, the multi-objective optimization design of magnetorquer with genetic algorithm (GA) is used under the constraint of limited mass and volume. Thirdly, based on the relation between the magnetic moment and the magnetic induction intensity, the measurement method of the magnetic moment is designed. Finally, the designed parameter is implemented. The test result showed that the designed magnetorquer has the qualities of high linearity, low remanence, and it well met the requirements of CubeSat standard. The designed magnetorquer successfully applied in several CubeSats indicates the reliability of this design scheme.

Aiming at the challenges of efficiently allocating the wireless resources to mass users under imperfect channel state information (CSI), an energy-efficient multiuser-multichannel matching algorithm involving the non-orthogonal multiple access (NOMA) technology is proposed. Considering the constraint of the user outage probability, a joint channel and power allocation optimization problem for cellular downlink NOMA system with imperfect CSI is formulated to maximize the system energy efficiency (EE). The established optimization problem with a probability constraint is transformed into a non-probability constrained optimization problem, from which the user-channel matching optimization problem is decoupled. The EE oriented user-channel matching optimization problem for NOMA system is mapped to the marriage matching problem, and an efficient and low complexity bilateral matching algorithm is thus proposed to realize the multiuser-multichannel dynamic matching. The simulation results show that the proposed matching algorithm achieves better performances than the traditional matching algorithms, which can achieve higher system EE, lower user outage probability and faster convergence speed. [ABSTRACT FROM AUTHOR]

Aiming to solve the topology vibration reduction optimization problems of cylindrical shells with constrained damping, a topology vibration reduction model was built based on variable density RAMP interpolation model, with the minimum model loss factor as optimal objective, and MAC factor was introduced to evaluate the step states of the vibration pattern, so as to find the optimal solution of vibration reduction within the design domain of the iterative lightweight constraints. The interpolation model of the objective sensitivity was deduced, the global optimization algorithm was calculated, and the global sensitivity topological variable optimization criterion method of ∞-norm was established to avoid the partial objective sensitivity of non-convex optimization function participating in the local optimal solution and jump of optimization iteration. The topological optimization analysis for constrained damping structures in vibration control of shell components was carried out by programming. The results show that the global optimization algorithm has wide optimization domain, stable and short iteration processes, and it is easy to obtain effective damping effectiveness by laying some damping materials. [ABSTRACT FROM AUTHOR]

In order to ensure the path continuity of redundant manipulators with constrained motion planning, this paper proposed a rapidly exploring random trees algorithm with progressive constraint extension ( PCE-RRT) for the constrained failure and path failure problems of direct interpolation and continuous interpolation. The algorithm introduced a progressive constrained extension method when performing tree expansion, which used the inverse kinematics method with the nearest point information, iteratively shortened the distance between the nearest point and the extended point while ensuring the task constraint, so that each extension could guarantee the constraint and continuity of the tree. PCE-RRT could make the final tree fit well into the constrained manifold subspace, and any two connected nodes in the search tree could satisfy the continuous condition. The simulation experiments verify the validity of the algorithm, and the results show that the proposed algorithm can provide a path solution that satisfied the constraints and continuity conditions for the manipulator constrained motion planning problem. [ABSTRACT FROM AUTHOR]

In view of the large number of unlabeled high-dimensional data, this paper studied unsupervised feature selection in machine learning, and proposed an unsupervised feature selection algorithm combining self-representation similarity matrix and manifold learning. Firstly, it constructed the similarity matrix by the self-expressiveness property of the data. Based on the idea that low-dimensional manifold could represent high-dimensional data structures, it established an unsupervised feature selection optimization model considering manifold learning. Secondly, in order to ensure the selection of more useful and sparse features, it used the 12, 1 norm to constrain the optimization model, so that features competed with each other and eliminated redundancy. Furthermore, it solved the optimization model by alternating iteration of variables, and proved convergence of the algorithm. Finally, it demonstrated the effectiveness of the proposed algorithm by comparison with other unsupervised feature algorithms on four data sets. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Architecture & Civil Engineering is the property of Chang'an Daxue Zazhishe and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The optimal regulation of the coupled system of water resources in the upper reaches of the Yangtze River involves the competing and incommensurable objectives of water supply, power generation and ecological water requirements. It is difficult to analyse and describe the mutual feedback covariance mechanism of the water supply, power generation and environment and to balance and optimize the regulation of multiple objective benefits. Based on the theory and method of multi-objective optimization and operational research, a method to study the mutual feed relationship among water supply, power generation and the environment is proposed using gradient analysis. The multiobjective constrained optimization method is used to obtain the Pareto optimal solution set of the joint optimal operation of the reservoir group in the upper reaches of the Yangtze River within the objective space of the water supply-power generation-environment, and the multi-objective space surface of the mutual feed relationship of the water supply-power generation-environment is constructed by interpolation. Thus, the first-order difference approximation is used to acquire the partial derivative function values of the water supply to the environment and power generation to quantify the gradient of the environmental response to changes in the water supply and power generation. Then, the mutual feed covariance relationship of the water supply-power generation-environment is analysed. This method provides a new approach for studying the multi-objective mutual feed relationship of the optimal operation of the reservoir group. [ABSTRACT FROM AUTHOR]

Wing structures with multiple plug-ins should meet the requirements of strength， stiffness， aeroelastic and assembly of equipment，it is difficult to get the optimal solution with traditional methods. In this paper，an analytical method is proposed to control the aeroelastic characteristics of the wing by restricting the bending and torsion stiffness of the wing section. The displacement and stability constraints sensitivity theories have been researched simultaneously. Then the new multi-constraints optimization process is developed and programmed based on the HAJIF platform. The method is verified by using a real wing model， and the results show that the proposed method can give the optimal design scheme on the unique static analysis model while the strength，stiffness and stability constraints are considered synchronously. [ABSTRACT FROM AUTHOR]