Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Nhiều chương trình CAD hiện nay cho phép tạo ra các mô hình ba chiều để có thể nhìn từ mọi góc độ. Các chương trình CAD mô hình hóa vật thể đặc tiên tiến là một hệ thống thiết kế hiện thực ảo. Những mô hình đặc như vậy có thể được dùng làm cơ sở cho các phân tích phần tử hữu hạn (FEA) và / hoặc tính toán động lực dòng chảy (CFD) của thiết kế. Cho đến ứng dụng gia công với trợ giúp máy tính (CAM), những mô hình này cũng có thể được dùng. | 174 R. Zlot and A. Stentz timestamping the start and end times of each algorithm. Results are presented in table 1. Table 1. Experimental results comparison of solution costs and execution times results shown are averages of the ratio of solution costs taken over 100 runs . Robots Areas CTT cFTL CTT cGR CTT COPT i Ti. TT ÌGRỈ TT tOPT tTT 2 1 .85 1.03 1.19 .21 3.9 117 4 2 .86 .92 .14 2.7 5 3 .88 1.00 .10 2.8 7 5 .88 1.01 .08 3.4 4 8 .91 1.10 .06 3.1 In terms of solution cost the task tree algorithm is 10-15 better than the FTL algorithm. One reason for this is that TT allows distributed replanning so the TT solution is intuitively expected to be no worse than the FTL - in the worst case no replanning is done by the task tree algorithm and the original tree decomposition is preserved4. In addition the task tree algorithm also has an advantage because it allows reallocation through task subcontracting permitting agents to discard tasks that they may have been too hasty in purchasing earlier on. It should also be noted that if the solutions are as we suspect close to optimal then a 10-15 margin of improvement is significant. We can see this in the 2-robot 1-area case in which we were able to compute the optimal solution. Here the task tree algorithm was only 19 worse than optimal as compared to FTL which was almost 40 worse than OPT. The execution time listed for the task tree algorithm tTT is the time taken to reach the local minimum cost although FTL appears to run much faster TT is an anytime algorithm and often reaches a lower cost than FTL long before it reaches its local minimum. On average the task tree algorithm and the GR algorithm produce about the same solution quality however the task tree algorithm is faster and does not rely on a central auctioneer. The execution time for the task tree algorithm shown in table reflects the time taken to reach the locally optimal solution. Though TT found its local optimum three to four times faster than GR the task tree .
