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Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University 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 Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University 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.)

As an important cornerstone of the fourth industrial revolution, the industrial Internet transforms isolated industrial systems into connected networks and is an important expansion direction for digital industrialization. Anomaly detection in the industrial Internet of things environment is of great significance for automated decision-making. To address the problem that most existing methods fail to effectively consider the complex unknown topological relationships between sensors and the multi-scale patterns inherent in the industrial IoT temporal data, an unsupervised anomaly detection method MSTSAD with multi-scale spatiotemporal feature fusion for industrial IoT temporal data is proposed, which firstly constructs a novel bi-directional spatiotemporal feature extraction module to sequentially captures the correlation and bidirec- tional dependency between multiple time series. Secondly, a multi- scale gated temporal convolutional neural network is designed to adaptively extract multi-scale temporal features of time series, and a dual affine projection is introduced to realize the cross- fusion of multi-scale temporal features and spatiotemporal features to enhance the feature extraction of the model on the original data. Finally, a variational self-encoder combined with adversarial training is proposed to amplify the reconstruction error of anomalies and enhance the anti-interference ability of the model to train data noise, which enhances the ability of model to discriminate anomalous data. Experiments are conducted on four publicly available datasets, GPW, ECG5000, Occupancy and SWaT, in comparison with five state-of-the-art methods, and the experimental results show that F1 scores of MSTSAD are enhanced by 0.015-0.047. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 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.)

Fuzzy Job-Shop scheduling problem is a classic embodiment of complex scheduling, and an excellent scheduling scheme designed for this problem can improve production efficiency. At present, the research on fuzzy Job-Shop scheduling problem mainly focused on single objective, this paper proposed an improved grey wolf optimization（IGWO） algorithm to solve the bi-objective fuzzy flexible Job-Shop scheduling problem to minimize the fuzzy completion time and the total load of fuzzy machines. This algorithm proposed a two-layer coding method to make IGWO discretization, designed a strategy based on HV contribution degree to improve population diversity. Then it used reinforcement learning method to determine global and local search parameters, improved two crossover operators to help individuals evolve in different update modes, and used two-level variable neighborhood and four replacement strategies to improve local search capability. Finally, this paper carried out several groups of experiments on several examples to verify the effectiveness of the improved strategy. In most test cases, the performance of IGWO algorithm is better than the comparison algorithm, with good convergence and distribution. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 order to obtain the high-quality collision free path of multi-robots, a multi-robot bilevel programming algorithm based on improved A* algorithm and conflict coordination strategy is proposed. Firstly, in the first layer of the algorithm, the heuristic function of the traditional A* algorithm is improved by introducing the dynamic weight factor combined with planned path information to avoid its blind search, so as to speed up the search speed. Through the screening mechanism and Bezier curve, the actual turning times of the robot are reduced and planned path is smoothed, and then the initial path of a single robot is obtained. Secondly, in the second layer of the algorithm, the time dimension is introduced based on the two-dimensional path to establish the robot path time map, so as to predict the conflict between robots. Finally, the conflict coordination strategy is used to coordinate the conflicts between robots and between robots and dynamic obstacles. The experimental results show that the bilevel programming algorithm can effectively reduce planned path search time and the number of turns, and obtain the smooth and collision free navigation path of each robot. [ABSTRACT FROM AUTHOR]

In order to meet the diversified travel demand of passengers and plan the tourism transportation network, this paper puts forward the perspective of passenger intermodal transport, a new road and short-haul general aviation transportation intermodal (road-air intermodal) mode was proposed. A bilevel programming model of road-air intermodal tourism transportation network was constructed. The upper layer mode aims at the shortest total travel time of passengers and total operating cost of the traffic network to designed the traffic route scheme. The lower layer model aimed at the shortest travel time of individual passenger and allocates passenger flow to the route. The proposed model was solved by genetic algorithm, and the example analysis shows that the road-air intermodal transportation network model is scientific, reasonable and feasible. [ABSTRACT FROM AUTHOR]

Copyright of Light Industry Machinery is the property of Light Industry Machinery 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 Power Generation Technology is the property of Power Generation Technology 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 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 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.)

Optimizing the vulnerable units in the traffic network is the premise to ensure the stable operation of the road network. Therefore, the improved evaluation index which could comprehensively reflect the vulnerability of road network from many aspects was selected, the relationship between the vulnerability index and the number of road sections and traffic volume was analyzed, and the bilevel programming model was used to describe the discrete traffic network design considering vulnerability. The upper model took the minimization of road network vulnerability as the optimization goal, and the lower model was the user equilibrium distribution model, by designing genetic algorithm and combining Frank-Wolfe algorithm. The example results show that when the investment amount is 3 million yuan, compared with the scheme taking the vulnerability of a single road section as the optimization objective, the optimization scheme proposed from the perspective of the whole road network can reduce the vulnerability of 13 road sections to the ideal value, while the former is only 7. At this time, the scheme can reduce the vulnerability of the road network by 38.5%, which is 9.1% more than the former; It is also found that the greater the origin-destination (OD) demand, the more construction funds need to be invested to reduce the road network vulnerability to the ideal value. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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 Central China Normal University is the property of Huazhong Normal University 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.)

For coyote optimization algorithm's global search ability was insufficient, easily plunged into local optimum, this paper proposed an improved coyote optimization algorithm. In the optimization process of coyote optimization algorithm, this improved algorithm introduced a deformed elite retention strategy and added the environmental impact factor in the growth process of coyote, then brought the grown coyotes into the Kent mapping to traverse the search space to strengthen the mining ability and search performance of the algorithm. Numerical experiments show that the improved algorithm has better perfor-mance. Taking the whole social and economic costs and carbon emissions as the decision-making objectives, this paper constructed a bi-level programming model for location and capacity of electric vehicle charging station, and used the improved coyote optimization algorithm to solve the programming model to verify the feasibility and effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute 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.)

Disaster preparedness measures can prepare for disaster relief to ensure that emergency supplies can reach the disaster area in a timely and effective manner. This paper proposed a bi-level programming emergency resource scheduling location-routing model with considering preparedness ( BLERSLR-P) In the model, the upper level aimed to minimize the total cost of supply station construction and operation, while the lower level aimed to minimize the cost of distribution route. This paper designed an improved bi-level salp swarm genetic algorithm (BLSSAGA) to solve this problem, combined the concept of iterative division to update the leader position, used the natural exponential inertia weight strategy to modify the control factor, used the chaotic map to update the follower position, and used Taguchi analysis to obtain reasonable values of parameters. Finally, this paper used bi-level salp swarm genetic algorithm ( BLSSAGA) and genetic particle swarm optimization algorithm ( GAPSO), particle swarm optimization algorithm( PSO), and immune optimization algorithm(IA ) to solve and compare and analyze the LRP data set in OR-Library, which verified the feasibility and effectiveness of the proposed model and algorithm. [ABSTRACT FROM AUTHOR]

Copyright of China Sciencepaper is the property of China Sciencepaper 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 order to solve the problem of obtaining high-precision tidal level in the port & waterway engineering far from the coast, the principle of medium and long distance GNSS positioning considering ocean water vapor, and the method coupled tide level extraction algorithm were studied and related software were developed. The instantaneous three-dimensional coordinates of GNSS antenna were measured by using PPK technology based on GPS and BDS, the instantaneous elevation of the sea surface was obtained by combining its coordinates in the hull coordinate system, the tide level in navigation was finally obtained through the Fourier transforming, wavelet filtering, and the conversion of the vertical datum. It has been proved by many tests and practical application that the accuracy of PPK technology in locating and acquiring tidal level in the medium and long distance waters can meet the requirements of horizontal positioning and tidal level in port & waterway engineering. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenzhen University Science & Engineering is the property of Editorial Department of Journal of Shenzhen University Science & 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 Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute 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 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.)

Recovery from major disasters is generally divided into an emergency recovery phase and a comprehensive recovery phase. The former faces multiple difficulties such as limits of time, funds and resources. The traditional research of post-disaster recovery of transportation networks lacks targeted research that combines the characteristics of the emergency recovery phase. To address these problems, a resilience-based optimization model of the recovery strategy in the emergency recovery phase for transportation networks is proposed. Firstly, two resilience metrics are proposed to measure resilience from both the recovery rapidity and the cumulative loss of network performance. Then, considering the interaction between system resilience at the upper level and user behavior at the lower level, a bi-level programming model for the transportation network recovery strategy in the emergency recovery phase is established. A special interactive bi-level algorithm is designed by combining the algorithm for the parallel machine scheduling problem and the algorithm for the user equilibrium problem. Finally, the validity of the proposed model is verified by a case study. The results indicate that the proposed model and algorithm can effectively determine the optimal recovery strategy in the emergency recovery phase for large-scale transportation networks with constraints of resources, funds, recovery goals, decision maker preference, etc. [ABSTRACT FROM AUTHOR]

In order to reduce property loss and human casualties, improve the satisfaction of the victims, this paper summarized the supplies scheduling problem under sudden disasters based on bi-level theory and from the perspective of emergency rescue. Focused on the emergency supplies scheduling, it carried out the review and discussion from the perspectives of post-disaster emergency status, emergency mate rial location-allocation, emergency supplies scheduling under different constraints, and the application of bi-level programming and swarm intelligence optimization algorithms in emergency supplies scheduling. The results showed that the research on the post-disaster emergency supplies scheduling currently focused on the single-level emergency network structure, and the objective function and constraint condition of the model were different from the actual situation. Combining the actual characteristics of the emergency supplies scheduling, this paper proposed some improvement suggestions. It considered the two-level emergency network structure, and then built a bi-level programming model to achieve joint optimization of the lower and upper level goals . [ABSTRACT FROM AUTHOR]

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.)

Quantity discount is introduced into sequential second-price auctions with two stochastically equivalent complementary objects. We study the impact of quantity discount on the buyers' equilibrium bidding strategies and expected surplus, set up the programming problem for the seller to choose the optimal quantity discount in order to maximize her ex ante expected revenue. Our analysis shows that: adopting quantity discount induces intense competition among the bidders, adequate quantity discount can increase the seller's ex ante expected revenue and optimal quantity discount decreases as the number of bidders increases. [ABSTRACT FROM AUTHOR]

This paper considered the semivectorial bilevel programming problem. By using Benson's method and dual theory of linear programming, the original problem was transformed into a single level optimization problem. This paper gave a definition of partial calmness of the transformed problem. Based on this definition, this paper constructed an exact penalized problem of the semivectorial bilevel programming problem, gave its optimality condition, and proposed an algorithm to solve it. Finally, this paper gave a numerical example to show that the algorithm is feasible. [ABSTRACT FROM AUTHOR]

The bilevel programming is applied to analyze the effectiveness of government organization in macroscopically controlling the emission permits market in order to optimize the emission permits resources allocation by utilizing the initial emission permits allocation and emission permits resources rate. A bilevel programming model regarding the most optimal income of the society and the emission permits users as the targets is established according to the behavior characteristics of emission permits users. On this basis, the optimal scheme of initial emission permits allocation and emission permits resources rate can be deduced consequently. An example is given to illustrate the idea of constructing and solving the model. [ABSTRACT FROM AUTHOR]

A principal-agent problem with asymmetric information is considered in this paper. Based on theories of ill-posed bilevel programming, the definition of ill-posed principal-agent problem is proposed. Then, a fuzzy interactive coordinating algorithm is presented for its optimistic formulation. Furthermore, a satisfactory contract is eventually derived for both principal and agent so that both are winners. Finally, an example is given to illustrate the rationality and the operability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Partial cooperation models have been studied for many years to solve the ill-posed bileved programming problems where the follower's optimal reaction is not unique. However, in these existed models, the followers cooperation level does not depend on the leaders decision. This paper proposes a new model to solve this deficiency. The numerical results show the new model has optimal solutions when the reaction set of the lower level is discrete, lower sem-continuous or non-lower semi-continuous. [ABSTRACT FROM AUTHOR]

Manufacture of multi-product pricing and ordering problem between the supplier and the retailer in a two-stage supply chain is multi-loss of risk decision-making problems, which can establish a bilevel programming model to be solved. This paper first studies a bilevel programming of multi-loss conditional value-at-risk model. For a multi-loss function and the corresponding weight value level, at a given confidence level, we define concept of the loss value does not exceed a given minimum value at risk (VaR) and the corresponding cumulative expected loss value (i.e. the CVaR losses value). Then, we set up a bilevel programming model of the multi-loss conditional value at risk, which the goal of the model is to solve an optimal strategy the minimum CVaR value of this model. This model can be solved more easily through another bilevel programming model to obtain the optimal solution. Finally, a multi- loss conditional value-at-risk model of multi-product pricing and ordering of a two-stage supply chain is presented. Calculated by two kinds of bread product sales data, we obtain a bread manufacturer's optimal wholesale price and optimal repurchase strategy, and retailers the optimal order quantity. [ABSTRACT FROM AUTHOR]