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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.)

Policy gradient algorithms suffer from the large variance of gradient estimation. the algorithm of policy gradient with parameter based exploration mitigates this problem to some extent. However, PGPE estimates its gradient based on the Monte Carlo, which requires a large number of samples to achieve the fairly stable policy update. And thus hinders its application in the real world problem. In order to further reduce the variance of policy gradient, the algorithm of function approximation for policy gradients with parameter-based exploration (PGPE-FA) implements the algorithm of PGPE in the Actor-Critic framework. More specifically, the proposed method utilized value function to estimate the policy gradient, instead of using trajectory samples to estimate the policy gradient as PGPE method does, thereby reducing the variance of gradient estimation. Finally, the experiment verifies that the proposed algorithm can reduce the variance of gradient estimation. [ABSTRACT FROM AUTHOR]

There are problems of interference between Devices-to-Devices (D2D) communication users and cellular users, mutu¬al interference between D2D communication users, and environmental interference caused by the existence of environmental obstacles in the D2D communication system assisted by Reconfigurable Intelligent Surface (RIS). In order to solve the problems, an optimization algorithm aiming at maximizing the total rate of the system is proposed to maintain the high quality of services among cellular users and D2D communication. Simulation experiments show that the total system speed under the tabu search- successive convex approximation algorithm is improved by 56% compared with the phase shift optimization algorithm. The to¬tal system speed under the tabu search-successive convex approximation algorithm is improved by 21. 2% compared with the power allocation algorithm. [ABSTRACT FROM AUTHOR]

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.)

We investigate the problem to schedule a set of precedence constrained jobs of unit size on an open-shop or on a flow-shop to minimize the makespan. The precedence constraints among the jobs are presented as a directed acyclic graph called the precedence graph. When the number of machines in the shop is part of the input, both problems are strongly NP-hard on general precedence graphs, but were proven polynomial-time solvable for some special precedence graphs such as intrees. In this paper, we characterize improved lower bounds on the minimum makespan in terms of the number of agreeable pairings among certain jobs and propose approximation algorithms based on a maximum matching among these jobs, so that every agreeable pair of jobs can be processed on different machines simultaneously. For open-shop with an arbitrary precedence graph and for flow-shop with a spine precedence graph, both achieved approximation ratios are 2 -- m, where m is the number of machines in the shop. [ABSTRACT FROM AUTHOR]

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.)

Aiming at the sensor network lifetime problem (SNLP), a sensor network coverage model and its data structure are proposed, and the problem is equivalent to its dual problem, namely minimum weight sensor coverage problem. Firstly, SNLP is constructed as a package linear programming. After finding different sensor coverage satisfying sensor network constraints, the sensor network life is maximized by allocating time for each sensor coverage. Secondly, for solving SNLP, three centralized solving methods are proposed, which are based on Garg- Konemann algorithm, greedy algorithm considering partial sensor coverage and constant approximation algorithm considering communication cost. At the same time, a distributed solving method based on global reshuffle is proposed. The reshuffle is triggered when the initial energy supply of a sensor drops to a certain predefined threshold value H among active, idle and intermediate vulnerable states, thus the sensor network lifetime is improved by using smart self- organizing monitoring schedules. Simulation results show that the proposed SNLP, which is based on sensor network coverage model and data structure, and its solving method can achieve preferable running time, network life and network overhead. [ABSTRACT FROM AUTHOR]

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 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 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.)

With the increasing maturity of wireless charging technology, especially the development of magnetic resonance wireless charging technology, the employment of mobile charging vehicles and wireless charging technology to replenish sensors' energy to ensure the continuous operation of wireless sensor networks has become a new research hotspot. This paper focused on how to schedule multiple charging vehicles to replenish energy to the sensors in a large-scale wireless sensor network. In order to balance the charging tasks of multiple charging vehicles and reduce the completion time of the whole charging task, the paper proposed the charging task completion time minimization problem, hoping to find K closed charging circles for K charging vehicles, so that the longest completion time among these K vehicles was the shortest. Since the charging task completion time minimization problem was an NP-hard problem and it was difficult to find an optimal solution in polynomial time, this paper proposed an approximation algorithm with a ratio of 5 for this problem. Finally, it demonstrated the performance of the algorithm by simulation experiments, and the experiments show that the actual approximation ratio of the proposed algorithm is less than 2. [ABSTRACT FROM AUTHOR]

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.)

For the nonlinear energy harvesting process in downlink multi-user simultaneous wireless information and power transfer network, this paper proposed a energy harvesting scheme using successive convex approximation. Considering the transmission security requirements of authorized users, the research aimed for maximizing the secrecy energy efficiency. It jointly optimized the security transmission rate of users and network energy consumption. To solve the non-convex optimization problem of multivariable coupling, it transformed non-convex function by Taylor series. In the theoretical framework combining successive convex approximation and Dinkelbach algorithm, it designed a resource allocation algorithm satisfying maximum secrecy energy efficiency requirement to obtain the minimum input power required by the authorized users. Simulation results show that the algorithm is effective in optimizing the secrecy energy efficiency of the system. The research provides a basis for the study of communication security and energy efficiency in more real SWIFT networks, such as multi-input multi-output (MIMO) or with incomplete channel state information. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She 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.)