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Full-Text Articles in Systems Science
Simulation Study Of Elevator Group Control Scheduling Based On Real-Time Occupancy Perception, Yiyong Han, Shiyu Wang, Yang Ye, Zhen Zhang, Fengque Pei, Minghai Yuan
Simulation Study Of Elevator Group Control Scheduling Based On Real-Time Occupancy Perception, Yiyong Han, Shiyu Wang, Yang Ye, Zhen Zhang, Fengque Pei, Minghai Yuan
Journal of System Simulation
Abstract: To address the conflict between car space allocation and peak passenger flow response efficiency in elevator group control scheduling, a multi-objective scheduling method based on proximal policy optimization (PPO) with real-time occupancy perception was proposed. A simulation environment considering car capacity constraints was constructed, and a reward-penalty mechanism with average passenger waiting time, system energy consumption, and car congestion as optimization objectives was designed. Based on this, state and action spaces were defined to form a PPO-based scheduling framework; a simulation platform integrating traffic flow visualization, policy scheduling, and performance evaluation was developed. Simulation results show that this method …
Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang
Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang
Journal of System Simulation
Abstract: To address the order splitting multi-objective hybrid flow-shop scheduling problem (OSMOHFSP), a dual-objective optimization model was formulated with the objectives of minimizing makespan and total order tardiness. Fixed sub-batch specification constraints were incorporated to reflect common splitting limitations in actual production. A sub-batch generation strategy based on a candidate set of sub-batch specifications was designed to efficiently filter feasible splitting combinations, effectively reducing the search space dimensionality and computational complexity. A hybrid multi-objective metaheuristic algorithm integrating NSGA-II and SA was proposed. The global search capability was enhanced by constructing two crossover and four mutation operators. An improved SA embedding …
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Journal of System Simulation
It is difficult for single-objective trajectory planning methods to meet the requirements of precision, diversity and complexity of robotic arms. A trajectory planning model based on an improved multi-objective differential evolution algorithm (guided multi-objective differential evolution, GMODE) algorithm is proposed. Cubic polynomial interpolation and B-spline curves are employed to construct multi-objective functions, while GMODE is adopted to overcome the limitations of traditional algorithms, such as insufficient population diversity, the tendency to fall into local optima, and slow convergence. A grouping strategy, parameter generation mechanism, and elite mutation based on fuzzy Cmeans clustering are introduced to optimize B-spline control nodes. …
Research On Pac-Bayes-Based A2c Algorithm For Multi-Objective Reinforcement Learning, Xiang Liu, Qiankun Jin
Research On Pac-Bayes-Based A2c Algorithm For Multi-Objective Reinforcement Learning, Xiang Liu, Qiankun Jin
Journal of System Simulation
Abstract: To address the theoretical challenges of exploration and exploitation trade-offs and uncertainty modeling in multi-objective reinforcement learning (MORL), this study developed a learning framework, MO-PAC, based on PAC-Bayes theory. By introducing a multi-objective stochastic Critic network and a dynamic preference mechanism, the framework extended the conventional A2C architecture, enabling adaptive and efficient approximation of complex Pareto fronts. Experimental results demonstrate that in multi-objective MuJoCo environments, MO-PAC outperforms baseline algorithms, achieving approximately 20% improvement in hypervolume and 60% increase in expected utility, while exhibiting superior convergence efficiency and robustness. It verifies both theoretical value and practical performance advantages in …
Automatic Multi-Objective Optimization Based On Dynamic Storage Location Allocation Strategy, Juan Chen, Wang Zheng, Qianqian Liu, Bin Lu
Automatic Multi-Objective Optimization Based On Dynamic Storage Location Allocation Strategy, Juan Chen, Wang Zheng, Qianqian Liu, Bin Lu
Journal of System Simulation
Abstract: Based on the dynamic storage allocation strategy, the two-stage optimization model is constructed with the whole warehouse as the main optimization body, in order to meet the safety and rationality of the storage allocation goals, and to meet the dispatching goals of the shortest operation time and the lowest energy consumption of each stacke. The upper and lower levels of the model are typical multi-objective optimization problems, and the ideal solution of the upper level model will be the initial condition of the lower level model. The multi-objective genetic algorithm is used to solve the ideal solution of the …
Optimization Of Cargo Location Allocation In Four-Way Shuttle Warehousing System Based On Two-Stage Hybrid Algorithm, Zisong Wu, Daofang Chang, Yuchun Gai
Optimization Of Cargo Location Allocation In Four-Way Shuttle Warehousing System Based On Two-Stage Hybrid Algorithm, Zisong Wu, Daofang Chang, Yuchun Gai
Journal of System Simulation
Abstract: To address issues such as the dense distribution of storage locations and the potential congestion of shuttle vehicles in the four-way shuttle dense storage system, a grid-based approach to the storage location distribution is developed. A location allocation model is then constructed with the goals of ensuring shelf stability, improving warehousing efficiency, and balancing equipment utilization. A twostage hybrid algorithm is designed for the model. In the first stage, the local search strategy of nondominant sequencing genetic algorithm(NSGA-II) is enhanced by incorporating the hill climbing algorithm to address a set of Pareto front sets. In the second stage, the …
Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang
Research On Mixed-Model Assembly Line Balancing Optimization Based On Hybrid Genetic Tabu Search Algorithm, Ke Wang, Sijia Guan, Xiyan Yin, Xixing Li, Hongtao Tang
Journal of System Simulation
Abstract: Aiming at the problem of unbalanced running load caused by idle or blocked workstations in the assembly line of mixed-flow hydraulic pump, a hybrid genetic tabu search algorithm solution and computer simulation verification method are proposed. A hybrid genetic tabu search algorithm with strong local search capability is designed with the optimization objectives of minimizing the production beats of the mixed-flow assembly line, the operational loads distributed among different workstations and the operational load smoothing indices of different products within the same workstation. The algorithm incorporates multi-fragment crossover and fragmentation of feasible solutions through Hamming distance mutation operations. The …
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Journal of System Simulation
Abstract: A multi-objective gait optimization method based on virtual prototype is proposed to address the difficulty of balancing personalisation and performance in gait planning for bipedal robots. A scale prototype of a planar underactuated biped robot is created according to the body structure of Chinese people, and an identification approach is used to determine the robot's exact inertial parameters. A virtual prototype of the robot is created, and three optimization goals—speed, energy use, and stability are developed. Using the enhanced NSGA-II algorithm, the Pareto optimal solution set for the robot multi-objective gait planning issue is produced. Numerous gaits that conform …
Platform Path Optimization Method Based On Cumulative Detection Probability Of Sonar Search, Xiang Wei, Xingxuan Liu, Dianzheng Fu, Tianji Yang, Jiaxuan Yang
Platform Path Optimization Method Based On Cumulative Detection Probability Of Sonar Search, Xiang Wei, Xingxuan Liu, Dianzheng Fu, Tianji Yang, Jiaxuan Yang
Journal of System Simulation
Abstract: To address the lack of research on the optimal path of mobile search platform to search for moving targets, this paper proposes a path optimization method of mobile search platform based on cumulative search probability theory. Based on the cumulative detection probability (CDP), one of the important criteria of sensor performance evaluation, a single-peak CDP calculation formula is constructed by using a time series correlation model, namely the (λ, σ) process model. A set of target motion scenarios are constructed, and the trajectory probability of target scenarios and their CDP at different time are corrected by Bayesian posterior probability. …
Multi-Objective Energy-Efficient No-Wait Flow Shop Scheduling Based On Hybrid Discrete State Transition Algorithm, Cong Wang, Jiaying Yu, Hongli Zhang
Multi-Objective Energy-Efficient No-Wait Flow Shop Scheduling Based On Hybrid Discrete State Transition Algorithm, Cong Wang, Jiaying Yu, Hongli Zhang
Journal of System Simulation
Abstract: A hybrid discrete state transition algorithm (HDSTA) is designed to solve the energyefficient no-wait flow shop scheduling problem (EENWFSP) minimizing makespan and total energy consumption. According to the characteristics of the problem, the coding method of job sequence and speed matrix is designed, and the heuristic algorithm is used to obtain the high-quality initial solution. According to the properties of EENWFSP, solving and allocating four discrete operators. The swap, shift and symmetry operators are embedded in secondary state transition are used for job sequence optimization, and the substitute operators are used for machine speed optimization. The speed substitute strategy …
Hybrid Evolutionary Multi-Objective Optimization Algorithm For Vehicle Routing Problem With Simultaneous Delivery And Pickup, Wenqiang Zhang, Xiaomeng Wang, Xiaoxiao Zhang, Guohui Zhang
Hybrid Evolutionary Multi-Objective Optimization Algorithm For Vehicle Routing Problem With Simultaneous Delivery And Pickup, Wenqiang Zhang, Xiaomeng Wang, Xiaoxiao Zhang, Guohui Zhang
Journal of System Simulation
Abstract: In order to provide reasonable and effective decision support for logistics enterprises in vehicle distribution route planning, a hybrid evolutionary multi-objective optimization algorithm combining a multi-region mixed-sampling strategy for global search and a local search based on individual route sequence differences is proposed for the problem. A reasonable mathematical model is constructed and the global search strategy is used to make the population individuals to converge quickly to the Pareto front from multiple directions, and the local search strategy is employed to guide the poorly performing individuals in the population to evolve towards the direction of better performing individuals, …
Real-Time Scheduling Method For Dynamic Flexible Job Shop Scheduling, Quan Jiang, Jingxuan Wei
Real-Time Scheduling Method For Dynamic Flexible Job Shop Scheduling, Quan Jiang, Jingxuan Wei
Journal of System Simulation
Abstract: A multi-objective dynamic flexible job shop scheduling problem model with machine breakdown and random jobs arrival is constructed to address the interference of dynamic events in manufacturing processing on the scheduling scheme, and a real-time scheduling method with multiobjective proximal policy optimization (MPPO) algorithm is proposed. The MPPO algorithm trains two agents, routing agent (RA) and sequencing agent (SA), for real-time scheduling and real-time processing of dynamic events. It employs a linear combination of weight vectors and reward vectors as reward signals and stores the agents' parameters for each weight vector to optimize multiple objectives. The required state information, …
Arterial Coordination Optimization Method Based On Vehicle Speed Guidance And Inductive Control, Mingjun Deng, Xinxia Hu, Xiang Li, Liping Xu
Arterial Coordination Optimization Method Based On Vehicle Speed Guidance And Inductive Control, Mingjun Deng, Xinxia Hu, Xiang Li, Liping Xu
Journal of System Simulation
Abstract: Arterial signal coordination is usually based on fixed belt speeds and time-of-day statistical flows. Actually, vehicle speeds and traffic flows are fluctuating, which causes to the mismatch between the signal scheme and the actual optimal belt speeds and traffic flow demands, and affects the intersection's traffic efficiency. Based on the vehicle infrastructure cooperation, by applying Maxband model and the maximum green wave bandwidth, the minimum number of arterial vehicle delays, arterial stops and the minor direction delays being the optimization objectives, a multi-objective optimization model for arterial signal coordination is established. Through using an improved multi-objective particle swarm algorithm …
Hybrid Flow Shop Scheduling With Limited Buffers Considering Energy Consumption And Transportation, Tingxin Wen, Tingyu Guan
Hybrid Flow Shop Scheduling With Limited Buffers Considering Energy Consumption And Transportation, Tingxin Wen, Tingyu Guan
Journal of System Simulation
Abstract: Aiming at the untimely production scheduling and excessive energy consumption during processing, a limited buffer hybrid flow shop scheduling optimization model is constructed. To minimize the makespan and total energy consumption of the workshop, the transport time, generalized energy consumption and buffer capacity being the constraints, and the on/off energy saving strategy applied to reduce the standby energy consumption, the feasibility of the optimization model are verified. A lion swarm optimization algorithm is designed, in which a population initialization method combining random generation and greedy selection is used to improve the initial solution quality and solution efficiency, the lion …
Hierarchical Guided Enhanced Multi-Objective Firefly Algorithm, Jia Zhao, Zhizhen Lai, Runxiu Wu, Zhihua Cui, Hui Wang
Hierarchical Guided Enhanced Multi-Objective Firefly Algorithm, Jia Zhao, Zhizhen Lai, Runxiu Wu, Zhihua Cui, Hui Wang
Journal of System Simulation
Abstract: The multi-objective firefly algorithm is easy to produce oscillation and aggregation phenomenon in the solution process, which leads to weak development ability and poor solution accuracy. This paper proposes a hierarchical guided enhanced multi-objective firefly algorithm (HGEMOFA). HGEMOFA builds a hierarchical guidance model, uses non-dominated sorting to obtain different levels of individuals. The individuals in the dominant layer are used to guide the evolution of the individuals in the inferior layer, the guidance direction is clear, the oscillation in the evolution process is solved, the aggregation phenomenon is reduced, and the convergence of the algorithm is enhanced. The Lévy …
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu
Journal of System Simulation
Abstract: Most of the new services in 5G mobile communication technologies, including smart homes, smart factories, and virtual reality, take place in indoor scenes. Therefore, how to quickly plan and build a 5G indoor distribution system with low construction cost and low power loss is of great significance for telecom operators. This paper establishes a mathematical planning model of a 5G indoor distribution system, which is closer to the actual scenario. The model aims to minimize the deployment cost and the maximum output signal power deviation between antennas, and the constraint is to meet the expected output signal power of …
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Journal of System Simulation
Abstract: Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by …
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Journal of System Simulation
Abstract: Aiming at the uncertainty and multi-periodicity of emergency supply distribution, a novel period vehicle routing problem(PVRP) multi-objective optimization model is built and a three-step optimization method is proposed. A triangular fuzzy number is used to eliminate the uncertainty. An AHP approach is used to transform the multi-objective function into the single objective function. An improved ACO algorithm is proposed to solve the single objective optimization problem. By classical data set, the time effectiveness of proposed method on emergency supply distribution problem is verified. The computational advantage in convergence speed is proved by the comparative analysis of the proposed …
Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang
Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang
Journal of System Simulation
Abstract: In order to improve the convergence of multi-objective optimization algorithm and the diversity of optimization solution set, and alleviate the flown down of population in target space, a multi-objective optimization algorithm based on multi-attribute elite individual game mechanism is proposed. This paper uses Pareto dominance relationship and multi-index to comprehensively screen elite individuals. The elite individual game mechanism with K-means clustering is integrated with cross and mutation strategy, which effectively improves the convergence and diversity of the algorithm. A detailed convergence analysis of the algorithm is performed to prove the convergence of the algorithm. Eight representative comparison algorithms are …
Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He
Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He
Journal of System Simulation
Abstract: An improved wolf pack algorithm is proposed for solving multi-objective scheduling optimization for flexible job shop problems. A multi-objective flexible job shop scheduling model is developed with the maximum completion time of the workpiece and the energy consumption of the machine as the optimization goals. An improved wolf pack algorithm is proposed for solving the shortcomings that traditional wolf pack algorithm is easy to fall into the local optimization. Through improving the intelligent behavior of the wolf pack algorithm, individual codes are designed from the two levels of job's process and machine, and POX(precedence operation crossover) cross operation is …
Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin
Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin
Journal of System Simulation
Abstract: In multi-objective optimization problems, as the number of decision variables increases, the optimization ability decreases significantly. To solve "dimension disaster", a large-scale multi-objective natural computation method based on dimensionality reduction and clustering is proposed. The decision variables are optimized by locally linear embedding(LLE) to obtain the representation of high-dimensional variables in the low-dimensional space, then the individuals are grouped through K-means to select the appropriate guide individuals for the population to strengthen the convergence and diversity. To verify the effectiveness, the method is applied to the multi-objective particle swarm optimization algorithm and the non-dominated sorting genetic algorithm. The convergence …
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Journal of System Simulation
Abstract: Based on the comprehensive consideration of economic indicators and environmental factors, the energy-efficient scheduling problem of multi-objective flexible job shop with uncertain processing time is studied. The interval number is used to describe uncertain processing time of the workpiece, and the optimization model for energy-efficient problem of interval flexible job shop scheduling is established to minimize the maximum interval completion time and total energy consumption. According to the domination relation of interval possibility degree, an effective interval multi-objective evolutionary algorithm is designed. The simulation experiments of the interval multi-objective evolutionary algorithm, SPEA-II and NSGA-II are carried out through 15 …
Optimization Of Household Electricity Consumption Period Based On Improved Multi-Objective Particle Swarm Optimization, Xiuying Yan, Miaomiao Dang
Optimization Of Household Electricity Consumption Period Based On Improved Multi-Objective Particle Swarm Optimization, Xiuying Yan, Miaomiao Dang
Journal of System Simulation
Abstract: Aiming at the household power load scheduling optimization, three objectives of the cost of electricity, satisfaction and user-side fluctuation degree are taken into comprehensive account. An improved adaptive weight multi-objective particle swarm optimization (IAW-MOPSO) algorithm is proposed to realize the scheduling optimization of household power load. The local improvement ability and global search ability of particle swarm optimization are balanced by updating the inertia weight of particle fitness value. The simulation results of five groups show that the proposed optimization strategy reduces the electricity charge by 29%, ensures the stability of electricity consumption in the peak period, and …
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
Journal of System Simulation
Abstract: During the COVID-19 pandemic, supply chain of manufacturing companies is facing more severe product demand uncertainty, which is manifested in the sharp increase in demand for certain types of products and the increased fluctuations in supply for raw materials. For this supply chain optimization problem with demand uncertainty, a multi-objective stochastic programming model is developed in order to maximize the total profit and product order fulfillment rate simultaneously in this paper. For solving the investigated problem, a new evolutionary multi-objective simulation optimization algorithm is proposed by combining the mechanism of NSGA-II and simulation computing budget allocation adaptively. Experimental …
Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai
Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai
Journal of System Simulation
Abstract: Aiming at the comprehensive problem of wobble of front suspension system and weave of rear suspension system of large displacement motorcycle at medium and high speed, a multi-objective optimization scheme based on sensitivity analysis and approximate modeling is proposed. The motorcycle model is established and the dynamics simulation is carried out. The lateral acceleration of front wheel's centroid position, the yaw rate and roll rate of whole vehicle's centroid position, which characterize the wobble and weave are the targets. The sensitivity analysis of suspension system parameters and the approximate modeling are carried out. Based on the analysis results, …
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Journal of System Simulation
Abstract: Aiming at the difficulty to obtain the optimal solution for the transmission ratio distribution of combined transmission, an optimization method for the transmission ratio of the combined multi-speed transmission based on the hybrid particle swarm optimization algorithm is proposed. Based on the multi-objective particle swarm algorithm, a leader population with a self-renewal mechanism is introduced to form a hybrid particle swarm algorithm. A multi-objective optimization model is established by taking the transmission ratio of each stage of single-speed transmission as a variable, combining the transmission chain layout, taking the driving power loss rate, specific fuel consumption loss …
Collaborative Optimization Of Production And Energy Consumption In Flexible Workshop, Ding Yu, Wang Yan, Zhicheng Ji
Collaborative Optimization Of Production And Energy Consumption In Flexible Workshop, Ding Yu, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: Considering the problem of the multi-objective constrained flexible job-shop,the NSGA-Ⅱalgorithm based on hybrid mutation operator is proposed.In view of NSGA-II algorithm being prone to premature convergence,poisson average and gaussian operators are introduced to improve the global and local optimization ability of the algorithm.The optimal scheme is selected from the set of pareto solutions by adopting the strategy of FAHP-IEVM,which is the combination of subjective and objective evaluation method. The modified algorithm is tested and compared by a series of ZDT test functions.The results show that the convergence and diversity of the revised algorithm are improved obviously.The effectiveness of …
Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He
Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He
Journal of System Simulation
Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …
Dynamic Environmental And Economic Dispatching Of Wind Farm Based On Multi-Objective, Le Wei, Xijin Li
Dynamic Environmental And Economic Dispatching Of Wind Farm Based On Multi-Objective, Le Wei, Xijin Li
Journal of System Simulation
Abstract: Wind farms are developing rapidly under the new policy on energy resources vigorously advocated by the state. Its output scheduling is very complex, and needs the integration of economic and environmental factors. Aiming at the large prediction error of wind power, in the dynamic environmental economic dispatch of wind farm, the cost of rotating reserve is taken into account within the generation cost, and the demand of wind power prediction error for rotating reserve capacity is taken into account within the constraint condition. Aiming at the minimum total cost of power generation, the minimum total pollutant emission and minimum …
Multi-Objective Topology Mapping Method For Network Emulation, Xiaofeng Wang, Chen Yang, Guangjie Zhang, Jianyu Chen
Multi-Objective Topology Mapping Method For Network Emulation, Xiaofeng Wang, Chen Yang, Guangjie Zhang, Jianyu Chen
Journal of System Simulation
Abstract: Network emulation is an important support for the verification of new network technology, and effective mapping is the key to the emulation network topology. Considering the multiple resource requirements, a multi-objective topology mapping method (MOTM) for network emulation topology is proposed to realize the effective physical resources utilization. The method analyzes the resource requirements of nodes and links, assigns corresponding weights, converts the mapping problem into the graph partitioning problem, divides the graph by multi-level graph partitioning method, and forms a mapping strategy through remote throughput threshold optimization adjustment. The automatic deployment is implemented based on the …