A new genetic algorithm named niche pseudo-parallel genetic algorithm （NPPGA） is presented for path evolution and genetic optimization of autonomous mobile robot. The NPPGA is an effective improvement to maintain th...A new genetic algorithm named niche pseudo-parallel genetic algorithm （NPPGA） is presented for path evolution and genetic optimization of autonomous mobile robot. The NPPGA is an effective improvement to maintain the population diversity as well for the sake of avoiding premature and strengthen parallelism of the population to accelerate the search process combined with niche genetic algorithms and pseudo-parallel genetic algorithms. The proposed approach is evaluated by robotic path optimization, which is a specific application of traveler salesman problem （TSP）. Experimental results indicated that a shortest path could be obtained in the practical traveling salesman problem named ＂Robot tour around Pekin＂, and the performance conducted by NPPGA is better than simple genetic algorithm （SGA） and distributed paralell genetic algorithms （DPGA）.展开更多
Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by ...Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.展开更多
To solve the combinatorial optimization problem of outer layout and inner connection integrated schemes in the design of hydraulic manifold blocks （ HMB）, a hybrid genetic simulated annealing algo- rithm based on ni...To solve the combinatorial optimization problem of outer layout and inner connection integrated schemes in the design of hydraulic manifold blocks （ HMB）, a hybrid genetic simulated annealing algo- rithm based on niche technology is presented. This hybrid algorithm, which combines genetic algorithm, simulated annealing algorithm and niche technology, has a strong capability in global and local search, and all extrema can be found in a short time without strict requests for preferences. For the complex restricted solid spatial layout problems in HMB, the optimizing mathematical model is presented. The key technologies in the integrated layout and connection design of HMB, including the realization of coding, annealing operation and genetic operation, are discussed. The framework of HMB optimal design system based on hybrid optimization strategy is proposed. An example is given to testify the effectiveness and feasibility of the algorithm.展开更多
The modified genetic algorithm was used for the optimal design of supporting structure in deep pits.Based on the common genetic algorithm, using niche technique and reserving the optimum individual the modified geneti...The modified genetic algorithm was used for the optimal design of supporting structure in deep pits.Based on the common genetic algorithm, using niche technique and reserving the optimum individual the modified genetic algorithm was presented. By means of the practical engineering, the modified genetic algorithm not only has more expedient convergence, but also can enhance security and operation efficiency.展开更多
In this paper, a new hybrid multi-objective evolutionary algorithm （MOEA）, the niched Pareto tabu search combined with a genetic algorithm （NPTSGA）, is proposed for the management of groundwater resources under va...In this paper, a new hybrid multi-objective evolutionary algorithm （MOEA）, the niched Pareto tabu search combined with a genetic algorithm （NPTSGA）, is proposed for the management of groundwater resources under variable density conditions. Relatively few MOEAs can possess global search ability contenting with intensified search in a local area. Moreover, the overall searching ability of tabu search （TS） based MOEAs is very sensitive to the neighborhood step size. The NPTSGA is developed on the thought of integrating the genetic algorithm （GA） with a TS based MOEA, the niched Pareto tabu search （NPTS）, which helps to alleviate both of the above difficulties. Here, the global search ability of the NPTS is improved by the diversification of candidate solutions arising from the evolving genetic algorithm population. Furthermore, the proposed methodology coupled with a density-dependent groundwater flow and solute transport simulator, SEAWAT, is developed and its performance is evaluated through a synthetic seawater intrusion management problem. Optimization results indicate that the NPTSGA offers a tradeoff between the two conflicting objectives. A key conclusion of this study is that the NPTSGA keeps the balance between the intensification of nondomination and the diversification of near Pareto-optimal solutions along the tradeoff curves and is a stable and robust method for implementing the multi-objective design of variable-density groundwater resources.展开更多
文摘A new genetic algorithm named niche pseudo-parallel genetic algorithm （NPPGA） is presented for path evolution and genetic optimization of autonomous mobile robot. The NPPGA is an effective improvement to maintain the population diversity as well for the sake of avoiding premature and strengthen parallelism of the population to accelerate the search process combined with niche genetic algorithms and pseudo-parallel genetic algorithms. The proposed approach is evaluated by robotic path optimization, which is a specific application of traveler salesman problem （TSP）. Experimental results indicated that a shortest path could be obtained in the practical traveling salesman problem named ＂Robot tour around Pekin＂, and the performance conducted by NPPGA is better than simple genetic algorithm （SGA） and distributed paralell genetic algorithms （DPGA）.
文摘Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.
基金Supported by the National Natural Science Foundation of China （No. 50375023）.
文摘To solve the combinatorial optimization problem of outer layout and inner connection integrated schemes in the design of hydraulic manifold blocks （ HMB）, a hybrid genetic simulated annealing algo- rithm based on niche technology is presented. This hybrid algorithm, which combines genetic algorithm, simulated annealing algorithm and niche technology, has a strong capability in global and local search, and all extrema can be found in a short time without strict requests for preferences. For the complex restricted solid spatial layout problems in HMB, the optimizing mathematical model is presented. The key technologies in the integrated layout and connection design of HMB, including the realization of coding, annealing operation and genetic operation, are discussed. The framework of HMB optimal design system based on hybrid optimization strategy is proposed. An example is given to testify the effectiveness and feasibility of the algorithm.
文摘The modified genetic algorithm was used for the optimal design of supporting structure in deep pits.Based on the common genetic algorithm, using niche technique and reserving the optimum individual the modified genetic algorithm was presented. By means of the practical engineering, the modified genetic algorithm not only has more expedient convergence, but also can enhance security and operation efficiency.
基金funded by the National Basic Research Program of China(the 973 Program,No.2010CB428803)the National Natural Science Foundation of China(Nos.41072175,40902069 and 40725010)
文摘In this paper, a new hybrid multi-objective evolutionary algorithm （MOEA）, the niched Pareto tabu search combined with a genetic algorithm （NPTSGA）, is proposed for the management of groundwater resources under variable density conditions. Relatively few MOEAs can possess global search ability contenting with intensified search in a local area. Moreover, the overall searching ability of tabu search （TS） based MOEAs is very sensitive to the neighborhood step size. The NPTSGA is developed on the thought of integrating the genetic algorithm （GA） with a TS based MOEA, the niched Pareto tabu search （NPTS）, which helps to alleviate both of the above difficulties. Here, the global search ability of the NPTS is improved by the diversification of candidate solutions arising from the evolving genetic algorithm population. Furthermore, the proposed methodology coupled with a density-dependent groundwater flow and solute transport simulator, SEAWAT, is developed and its performance is evaluated through a synthetic seawater intrusion management problem. Optimization results indicate that the NPTSGA offers a tradeoff between the two conflicting objectives. A key conclusion of this study is that the NPTSGA keeps the balance between the intensification of nondomination and the diversification of near Pareto-optimal solutions along the tradeoff curves and is a stable and robust method for implementing the multi-objective design of variable-density groundwater resources.
