Path Planning Based on Dynamic Sub-population Pseudo-Parallel Genetic Algorithm

Author(s):  
Lei Li ◽  
Yuemei Ren ◽  
Changyu Yang
2014 ◽  
pp. 1-13 ◽  
Author(s):  
Panpan Cai ◽  
Yiyu Cai ◽  
Indhumathi Chandrasekaran ◽  
Jianmin Zheng

Robotica ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 823-836 ◽  
Author(s):  
Hamed Shorakaei ◽  
Mojtaba Vahdani ◽  
Babak Imani ◽  
Ali. Gholami

SUMMARYThe current paper presents a path planning method based on probability maps and uses a new genetic algorithm for a group of UAVs. The probability map consists of cells that display the probability which the UAV will not encounter a hostile threat. The probability map is defined by three events. The obstacles are modeled in the probability map, as well. The cost function is defined such that all cells are surveyed in the path track. The simple formula based on the unique vector is presented to find this cell position. Generally, the cost function is formed by two parts; one part for optimizing the path of each UAV and the other for preventing UAVs from collision. The first part is a combination of safety and length of path and the second part is formed by an exponential function. Then, the optimal paths of each UAV are obtained by the genetic algorithm in a parallel form. According to the dimensions of path planning, genetic encoding has two or three indices. A new genetic operator is introduced to select an appropriate pair of chromosome for crossover operation. The effectiveness of the method is shown by several simulations.


2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Bailing Liu ◽  
Hui Chen ◽  
Yanhui Li ◽  
Xiang Liu

Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.


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