This paper states a new metaheuristic based on Deterministic Finite Automata （DFA） for the multi - objective optimization of combinatorial problems. First, a new DFA named Multi - Objective Deterministic Finite Auto...This paper states a new metaheuristic based on Deterministic Finite Automata （DFA） for the multi - objective optimization of combinatorial problems. First, a new DFA named Multi - Objective Deterministic Finite Automata （MDFA） is defined. MDFA allows the representation of the feasible solutions space of combinatorial problems. Second, it is defined and implemented a metaheuritic based on MDFA theory. It is named Metaheuristic of Deterministic Swapping （MODS）. MODS is a local search strategy that works using a MDFA. Due to this, MODS never take into account unfeasible solutions. Hence, it is not necessary to verify the problem constraints for a new solution found. Lastly, MODS is tested using well know instances of the Bi-Objective Traveling Salesman Problem （TSP） from TSPLIB. Its results were compared with eight Ant Colony inspired algorithms and two Genetic algorithms taken from the specialized literature. The comparison was made using metrics such as Spacing, Generational Distance, Inverse Generational Distance and No-Dominated Generation Vectors. In every case, the MODS results on the metrics were always better and in some of those cases, the superiority was 100%.展开更多
Pulping production process produces a large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implemen...Pulping production process produces a large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implement cleaner production by using modeling and optimization technology. This paper studies the modeling and multi\|objective genetic algorithms for continuous digester process. First, model is established, in which environmental pollution and saving energy factors are considered. Then hybrid genetic algorithm based on Pareto stratum\|niche count is designed for finding near\|Pareto or Pareto optimal solutions in the problem and a new genetic evaluation and selection mechanism is proposed. Finally using the real data from a pulp mill shows the results of computer simulation. Through comparing with the practical curve of digester,this method can reduce the pollutant effectively and increase the profit while keeping the pulp quality unchanged.展开更多
针对动态覆盖问题可以转化为多目标优化问题,提出一种解决多目标优化的连续空间蚁群算法(Continuous Space Ant Colony System,CSACS).该算法通过随机划分过程,对连续解空间划分为多个子空间,分别在不同子空间利用蚁群进行区域内以及区...针对动态覆盖问题可以转化为多目标优化问题,提出一种解决多目标优化的连续空间蚁群算法(Continuous Space Ant Colony System,CSACS).该算法通过随机划分过程,对连续解空间划分为多个子空间,分别在不同子空间利用蚁群进行区域内以及区域间搜索Pareto最优解,为了保证最优解的多样性,引入小生境策略进行Pareto最优解适应度更新.实验表明,在不同网络规模和迭代次数下,区域覆盖度和网络寿命相对于传统经典算法有较好改进.字数以250字以上为宜.请不要在摘要中引用参考文献和英文缩略语.展开更多
文摘This paper states a new metaheuristic based on Deterministic Finite Automata （DFA） for the multi - objective optimization of combinatorial problems. First, a new DFA named Multi - Objective Deterministic Finite Automata （MDFA） is defined. MDFA allows the representation of the feasible solutions space of combinatorial problems. Second, it is defined and implemented a metaheuritic based on MDFA theory. It is named Metaheuristic of Deterministic Swapping （MODS）. MODS is a local search strategy that works using a MDFA. Due to this, MODS never take into account unfeasible solutions. Hence, it is not necessary to verify the problem constraints for a new solution found. Lastly, MODS is tested using well know instances of the Bi-Objective Traveling Salesman Problem （TSP） from TSPLIB. Its results were compared with eight Ant Colony inspired algorithms and two Genetic algorithms taken from the specialized literature. The comparison was made using metrics such as Spacing, Generational Distance, Inverse Generational Distance and No-Dominated Generation Vectors. In every case, the MODS results on the metrics were always better and in some of those cases, the superiority was 100%.
基金TheNationNaturalScienceFoundationofChina (No .6 9974 0 34)
文摘Pulping production process produces a large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implement cleaner production by using modeling and optimization technology. This paper studies the modeling and multi\|objective genetic algorithms for continuous digester process. First, model is established, in which environmental pollution and saving energy factors are considered. Then hybrid genetic algorithm based on Pareto stratum\|niche count is designed for finding near\|Pareto or Pareto optimal solutions in the problem and a new genetic evaluation and selection mechanism is proposed. Finally using the real data from a pulp mill shows the results of computer simulation. Through comparing with the practical curve of digester,this method can reduce the pollutant effectively and increase the profit while keeping the pulp quality unchanged.
文摘针对动态覆盖问题可以转化为多目标优化问题,提出一种解决多目标优化的连续空间蚁群算法(Continuous Space Ant Colony System,CSACS).该算法通过随机划分过程,对连续解空间划分为多个子空间,分别在不同子空间利用蚁群进行区域内以及区域间搜索Pareto最优解,为了保证最优解的多样性,引入小生境策略进行Pareto最优解适应度更新.实验表明,在不同网络规模和迭代次数下,区域覆盖度和网络寿命相对于传统经典算法有较好改进.字数以250字以上为宜.请不要在摘要中引用参考文献和英文缩略语.
