Development of a parallel optimization method based on genetic simulated annealing algorithm

Advances in Mechanical Engineering

Zhang

Ban

et al. 2013

The effect of driver's physiological and psychological characteristics on traffic safety is represented mainly as driver's propensity. Previous researches focus mostly on psychology test and its influence on traffic safety from relative static and macroscopic perspective. However, in the field of vehicle active safety, there are few studies on driver's affective measurement and computing from microcosmic and dynamic perspective, and previous researchers did not consider the influence of environment. The emphasis is about situation factors which directly influence driver's affection in all environment factors under two-lane condition. Various experiments are designed to collect driver's microdynamic information, and characteristics of driver's propensity toward different environments are extracted using genetic simulated annealing algorithm. Results show that the method can provide a basis to establish dynamic recognition model of driver's propensity further which is adapted to multilane environment.

Section: Feature Extraction Methods Based On Genetic Simulatedmentioning

confidence: 99%

Dynamic Feature Extraction Method of Driver's Propensity under Complicated Vehicle Group

Advances in Mechanical Engineering

Zhang

Ban

et al. 2013

“…2) Searching the approximate optimal solution with the simulatiom annealing algorithm [5,6] The Floyd [7] algorithm is used to solve the path and the shortest distance between any two location points in the figure after the group is solved. Accordingly, an equivalent network diagram is constructed with containing all customer location points.…”

Section: ) Grouping the Customers By Clustering Algorithm [4]mentioning

confidence: 99%

Goods distribution based on simulation annealing and dynamic programming

2013 Ninth International Conference on Natural Computation (ICNC)

Feng

Niu

et al. 2013

The optimization problem of goods distribution is an important issue in the modern logistics industry. In this paper, we propose a novel and effective mathematical model to solve the optimization problem. Furthermore, we present a novel method that can effectively combine the simulation annealing algorithm with dynamic programming algorithm to achieve the optimized results of the mathematical model. First, the minimum number of vehicles is roughly estimated. According to the minimum number of vehicles, we group the customers with clustering algorithm. Secondly, the shortest distance between any two vertexes for every group is calculated by the Floyd algorithm. The equivalent network graph is constructed based on the shortest distance. In addition, a Hamilton circle is solved by the simulating annealing algorithm from the equivalent network graph. An approximate optimal solution of the vehicles delivery route is obtained by integrating the points in both ends. Finally, the optimal route of every vehicle is integrated and performs local adjustment by the dynamic programming. Therefore, the globally optimal solution of the whole problem is obtained. The experimental results show that the proposed method is more effectively solve the goods distribution problems than other traditional algorithms.

“…Distributed GA which depends less on objects and has high searching performance [37] is used for identification. The mode parameters are encoded into binary GA individuals.…”

Section: Identification Through Gamentioning

confidence: 99%

Modeling the yaw dynamics of an unmanned helicopter through modes partition method

Sci. China Technol. Sci.

Xia

Yuan

et al. 2011

The main difficulties in modeling yaw dynamics of a helicopter arise from the high nonlinearities, cross-couplings and dynamic uncertainties of these aerocraft. This paper proposes a new identification approach for yaw dynamics modeling through modes partition method (MPM) with a concentrated search space limited by implicit human factors. Working from first principles and basic aerodynamics, the nonlinear equations of motion for yaw dynamics is derived. The model is linearized and transformed into a combination of dynamic modes, whose coefficients are identified from real-flight data through distributed genetic algorithm (DGA). The effectiveness of the approach is validated in terms of the identified model which can accurately capture the dynamic characters of the helicopter. Time-and frequency-domain results clearly demonstrate the potential of MPM in modeling such complex systems. dynamics, identification, unmanned helicopter, genetic algorithm Citation:Wang G L, Xia H, Yuan X M, et al. Modeling the yaw dynamics of an unmanned helicopter through modes partition method.