This paper introduces an optimization method(SCE-SR)that combines shuffled complex evolution(SCE)and stochastic ranking(SR)to solve constrained reservoir scheduling problems,ranking individuals with both objectives an...This paper introduces an optimization method(SCE-SR)that combines shuffled complex evolution(SCE)and stochastic ranking(SR)to solve constrained reservoir scheduling problems,ranking individuals with both objectives and constrains considered.A specialized strategy is used in the evolution process to ensure that the optimal results are feasible individuals.This method is suitable for handling multiple conflicting constraints,and is easy to implement,requiring little parameter tuning.The search properties of the method are ensured through the combination of deterministic and probabilistic approaches.The proposed SCE-SR was tested against hydropower scheduling problems of a single reservoir and a multi-reservoir system,and its performance is compared with that of two classical methods(the dynamic programming and genetic algorithm).The results show that the SCE-SR method is an effective and efficient method for optimizing hydropower generation and locating feasible regions quickly,with sufficient global convergence properties and robustness.The operation schedules obtained satisfy the basic scheduling requirements of reservoirs.展开更多
Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, socia...Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are discussed.This paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.展开更多
Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of p...Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of pas- sengers at the current stop and at the following stops is con- structed and a new heuristic algorithm, shuffled complex evo- lution method developed at the University of Arizona （SCE- UA）, is adopted to optimize the holding times of early buses. Results show that the improved holding strategy can provide better performance compared with a traditional schedule- based holding strategy and no-control strategy. The compu- tational results are also evidence of the feasibility of using SCE-UA in optimizing the holding times of early buses at a stop.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2016YFC0401702)the Fundamental Research Funds for the Central Universities(Grant No.2018B11214)the National Natural Science Foundation of China(Grants No.51379059 and 51579002)
文摘This paper introduces an optimization method(SCE-SR)that combines shuffled complex evolution(SCE)and stochastic ranking(SR)to solve constrained reservoir scheduling problems,ranking individuals with both objectives and constrains considered.A specialized strategy is used in the evolution process to ensure that the optimal results are feasible individuals.This method is suitable for handling multiple conflicting constraints,and is easy to implement,requiring little parameter tuning.The search properties of the method are ensured through the combination of deterministic and probabilistic approaches.The proposed SCE-SR was tested against hydropower scheduling problems of a single reservoir and a multi-reservoir system,and its performance is compared with that of two classical methods(the dynamic programming and genetic algorithm).The results show that the SCE-SR method is an effective and efficient method for optimizing hydropower generation and locating feasible regions quickly,with sufficient global convergence properties and robustness.The operation schedules obtained satisfy the basic scheduling requirements of reservoirs.
基金by National Key Research and Development Project,Ministry of Science and Technology,China(No.2018AAA0101300)National Natural Science Foundation of China(Nos.61976093 and 61873097)+1 种基金Guangdong-Hong Kong Joint Innovative Platform of Big Data and Computational Intelligence(No.2018B050502006)Guangdong Natural Science Foundation Research Team(No.2018B030312003).
文摘Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are discussed.This paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.
文摘Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of pas- sengers at the current stop and at the following stops is con- structed and a new heuristic algorithm, shuffled complex evo- lution method developed at the University of Arizona （SCE- UA）, is adopted to optimize the holding times of early buses. Results show that the improved holding strategy can provide better performance compared with a traditional schedule- based holding strategy and no-control strategy. The compu- tational results are also evidence of the feasibility of using SCE-UA in optimizing the holding times of early buses at a stop.
