For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best coo...For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.展开更多
Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutio...Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions diversity.In this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision space.We first extend a latest single-objective fireworks algorithm to handle MMOPs.Then we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special archives.Finally,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization problems.Experimental results show that the proposed algorithm is superior to compared algorithms in solving them.Also,its runtime is less than its peers'.展开更多
针对同时送取货的选址路径问题(Location-routing Problem with Simultaneous Pickup and Delivery,LRPSPD),设计一种改进烟花算法(Improved Firework Algorithm,IFWA)求解。首先,考虑仓库建设、车辆启用、车辆路径等成本因素,建立最小...针对同时送取货的选址路径问题(Location-routing Problem with Simultaneous Pickup and Delivery,LRPSPD),设计一种改进烟花算法(Improved Firework Algorithm,IFWA)求解。首先,考虑仓库建设、车辆启用、车辆路径等成本因素,建立最小成本的LRPSPD模型,该模型强调需求点的送货需求和取货需求只能由一辆车同时进行服务。其次,设计一种改进烟花算法,该算法结合贪心聚类算法生成初始解,由烟花爆炸算子操作生成邻域解,利用变异操作协助产生新种群。最后,通过使用混合免疫算法、模拟退火算法求解相同算例,对结果进行分析比较,验证模型的可行性和改进算法的有效性。展开更多
Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data....Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data.In this study,a multi-field co-simulation data extractionmethod based on adaptive infinitesimal elements is proposed.Themultifield co-simulation dataset based on related infinitesimal elements is constructed,and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction.Based on the fireworks algorithm,the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive calculation of data extraction micro-step length.The multi-field co-simulation data extraction process based on adaptive microelement is established and applied to the data extraction process of the multi-field co-simulation dataset of the sintering furnace.Compared with traditional data extraction methods for multi-field co-simulation,the approximate model constructed by the data extracted from the proposed method has higher construction efficiency.Meanwhile,the relative maximum absolute error,root mean square error,and coefficient of determination of the approximationmodel are better than those of the approximation model constructed by the data extracted from traditional methods,indicating higher accuracy,it is verified that the proposed method demonstrates sound adaptability and extraction efficiency.展开更多
基金supported by the National Natural Science Foundation of China(61571149)the Special China Postdoctoral Science Foundation(2015T80325)+2 种基金the Heilongjiang Postdoctoral Fund(LBH-Z13054)the China Scholarship Council and the Fundamental Research Funds for the Central Universities(HEUCFP201772HEUCF160808)
文摘For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.
基金supported in part by the National Natural Science Foundation of China(62071230,62061146002)the Natural Science Foundation of Jiangsu Province(BK20211567)the Deanship of Scientific Research(DSR)at King Abdulaziz University(KAU),Jeddah,Saudi Arabia(FP-147-43)。
文摘Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions diversity.In this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision space.We first extend a latest single-objective fireworks algorithm to handle MMOPs.Then we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special archives.Finally,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization problems.Experimental results show that the proposed algorithm is superior to compared algorithms in solving them.Also,its runtime is less than its peers'.
文摘针对同时送取货的选址路径问题(Location-routing Problem with Simultaneous Pickup and Delivery,LRPSPD),设计一种改进烟花算法(Improved Firework Algorithm,IFWA)求解。首先,考虑仓库建设、车辆启用、车辆路径等成本因素,建立最小成本的LRPSPD模型,该模型强调需求点的送货需求和取货需求只能由一辆车同时进行服务。其次,设计一种改进烟花算法,该算法结合贪心聚类算法生成初始解,由烟花爆炸算子操作生成邻域解,利用变异操作协助产生新种群。最后,通过使用混合免疫算法、模拟退火算法求解相同算例,对结果进行分析比较,验证模型的可行性和改进算法的有效性。
基金This work is supported by the NationalNatural Science Foundation of China(No.52075350)the Major Science and Technology Projects of Sichuan Province(No.2022ZDZX0001)the Special City-University Strategic Cooperation Project of Sichuan University and Zigong Municipality(No.2021CDZG-3).
文摘Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data.In this study,a multi-field co-simulation data extractionmethod based on adaptive infinitesimal elements is proposed.Themultifield co-simulation dataset based on related infinitesimal elements is constructed,and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction.Based on the fireworks algorithm,the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive calculation of data extraction micro-step length.The multi-field co-simulation data extraction process based on adaptive microelement is established and applied to the data extraction process of the multi-field co-simulation dataset of the sintering furnace.Compared with traditional data extraction methods for multi-field co-simulation,the approximate model constructed by the data extracted from the proposed method has higher construction efficiency.Meanwhile,the relative maximum absolute error,root mean square error,and coefficient of determination of the approximationmodel are better than those of the approximation model constructed by the data extracted from traditional methods,indicating higher accuracy,it is verified that the proposed method demonstrates sound adaptability and extraction efficiency.
