Optimized task scheduling is one of the most important challenges to achieve high performance in multiprocessor environments such as parallel and distributed systems. Most introduced task-scheduling algorithms are bas...Optimized task scheduling is one of the most important challenges to achieve high performance in multiprocessor environments such as parallel and distributed systems. Most introduced task-scheduling algorithms are based on the so-called list scheduling technique. The basic idea behind list scheduling is to prepare a sequence of nodes in the form of a list for scheduling by assigning them some priority measurements, and then repeatedly removing the node with the highest priority from the list and allocating it to the processor providing the earliest start time （EST）. Therefore, it can be inferred that the makespans obtained are dominated by two major factors： （1） which order of tasks should be selected （sequence subproblem）; （2） how the selected order should be assigned to the processors （assignment subproblem）. A number of good approaches for overcoming the task sequence dilemma have been proposed in the literature, while the task assignment problem has not been studied much. The results of this study prove that assigning tasks to the processors using the traditional EST method is not optimum; in addition, a novel approach based on the ant colony optimization algorithm is introduced, which can find far better solutions.展开更多
This paper investigates the cost control problem of congestion management model in the real-time power systems. An improved optimal congestion cost model is built by introducing the congestion factor in dealing with t...This paper investigates the cost control problem of congestion management model in the real-time power systems. An improved optimal congestion cost model is built by introducing the congestion factor in dealing with the cases: opening the generator side and load side simultaneously. The problem of real-time congestion management is transformed to a nonlinear programming problem. While the transmission congestion is maximum, the adjustment cost is minimum based on the ant colony algorithm, and the global optimal solu-tion is obtained. Simulation results show that the improved optimal model can obviously reduce the adjust-ment cost and the designed algorithm is safe and easy to implement.展开更多
Personalized social matching systems can be seen as recommender systems that recommend people to others in the social networks, with desirable skills/characteristics. In this work, an algorithm based on Ant Colony is ...Personalized social matching systems can be seen as recommender systems that recommend people to others in the social networks, with desirable skills/characteristics. In this work, an algorithm based on Ant Colony is proposed to solve the optimization problem of clustering/matching people in a social network specifically designed for this purpose;during this process, their personal characteristics and preferences (and the degree of importance thereof) are taken into account. The numerical results indicate that the proposed algorithm can successfully perform clustering with a variable number of individuals.展开更多
The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and G...The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.展开更多
In this paper, systematic review on Ant System (AS) algorithm research and application is made, and the authors works of introducing As algorithm into continuous space application are summarized. Then the applicabil...In this paper, systematic review on Ant System (AS) algorithm research and application is made, and the authors works of introducing As algorithm into continuous space application are summarized. Then the applicability characters of AS in continuous space optimization problems are also discussed.展开更多
In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the disco...In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.展开更多
A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from th...A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.展开更多
Recent development of technologies and methodologies on distributed spacecraft systems enable the small satellite network systems by supporting integrated navigation, communications and control tasks. The distributed ...Recent development of technologies and methodologies on distributed spacecraft systems enable the small satellite network systems by supporting integrated navigation, communications and control tasks. The distributed sensing data can be communicated and processed autonomously among the network systems. Due to the size, density and dynamic factors of small satellite networks, the traditional network communication framework is not well suited for distributed small satellites. The paper proposes a novel swarm intelligence based networking framework by using Ant colony optimization. The proposed network framework enables self-adaptive routing, communications and network reconstructions among small satellites. The simulation results show our framework is suitable for dynamic factors in distributed small satellite systems. The proposed schemes are adaptive and scalable to network topology and achieve good performance in different network scenarios.展开更多
基金Project supported by Sama Technical and Vocational Training College,Islamic Azad University,Shoushtar Branch,Shoushtar,Iran
文摘Optimized task scheduling is one of the most important challenges to achieve high performance in multiprocessor environments such as parallel and distributed systems. Most introduced task-scheduling algorithms are based on the so-called list scheduling technique. The basic idea behind list scheduling is to prepare a sequence of nodes in the form of a list for scheduling by assigning them some priority measurements, and then repeatedly removing the node with the highest priority from the list and allocating it to the processor providing the earliest start time （EST）. Therefore, it can be inferred that the makespans obtained are dominated by two major factors： （1） which order of tasks should be selected （sequence subproblem）; （2） how the selected order should be assigned to the processors （assignment subproblem）. A number of good approaches for overcoming the task sequence dilemma have been proposed in the literature, while the task assignment problem has not been studied much. The results of this study prove that assigning tasks to the processors using the traditional EST method is not optimum; in addition, a novel approach based on the ant colony optimization algorithm is introduced, which can find far better solutions.
文摘This paper investigates the cost control problem of congestion management model in the real-time power systems. An improved optimal congestion cost model is built by introducing the congestion factor in dealing with the cases: opening the generator side and load side simultaneously. The problem of real-time congestion management is transformed to a nonlinear programming problem. While the transmission congestion is maximum, the adjustment cost is minimum based on the ant colony algorithm, and the global optimal solu-tion is obtained. Simulation results show that the improved optimal model can obviously reduce the adjust-ment cost and the designed algorithm is safe and easy to implement.
文摘Personalized social matching systems can be seen as recommender systems that recommend people to others in the social networks, with desirable skills/characteristics. In this work, an algorithm based on Ant Colony is proposed to solve the optimization problem of clustering/matching people in a social network specifically designed for this purpose;during this process, their personal characteristics and preferences (and the degree of importance thereof) are taken into account. The numerical results indicate that the proposed algorithm can successfully perform clustering with a variable number of individuals.
文摘The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.
文摘In this paper, systematic review on Ant System (AS) algorithm research and application is made, and the authors works of introducing As algorithm into continuous space application are summarized. Then the applicability characters of AS in continuous space optimization problems are also discussed.
文摘In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.
文摘A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.
文摘Recent development of technologies and methodologies on distributed spacecraft systems enable the small satellite network systems by supporting integrated navigation, communications and control tasks. The distributed sensing data can be communicated and processed autonomously among the network systems. Due to the size, density and dynamic factors of small satellite networks, the traditional network communication framework is not well suited for distributed small satellites. The paper proposes a novel swarm intelligence based networking framework by using Ant colony optimization. The proposed network framework enables self-adaptive routing, communications and network reconstructions among small satellites. The simulation results show our framework is suitable for dynamic factors in distributed small satellite systems. The proposed schemes are adaptive and scalable to network topology and achieve good performance in different network scenarios.
