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These are the user uploaded subtitles that are being translated: 1 00:00:00.07 --> 00:00:01.09 - [Instructor] Each Generative Design 2 00:00:01.09 --> 00:00:04.08 study has its unique design criteria. 3 00:00:04.08 --> 00:00:06.04 And this depends on the problem 4 00:00:06.04 --> 00:00:08.03 that the study is attempting to solve 5 00:00:08.03 --> 00:00:10.07 and the type of method that's selected. 6 00:00:10.07 --> 00:00:13.04 So let's take a closer look at the design criteria 7 00:00:13.04 --> 00:00:15.05 for the workplace study that we created 8 00:00:15.05 --> 00:00:17.00 in a previous lesson. 9 00:00:17.00 --> 00:00:19.00 As we learned in the last lesson, 10 00:00:19.00 --> 00:00:21.09 each different study method type has its unique set 11 00:00:21.09 --> 00:00:25.04 of inputs, which define how the study will run. 12 00:00:25.04 --> 00:00:28.05 These are made up of and can include selections, 13 00:00:28.05 --> 00:00:32.09 variables, goals, constraints, and constants. 14 00:00:32.09 --> 00:00:35.04 Selections are items that need to be selected 15 00:00:35.04 --> 00:00:38.03 from within Revit for the study to run. 16 00:00:38.03 --> 00:00:40.08 In this example, we require a room 17 00:00:40.08 --> 00:00:42.06 and a desk family instance, 18 00:00:42.06 --> 00:00:45.07 which is displayed here in the select box. 19 00:00:45.07 --> 00:00:48.06 As we can see, neither of these have been selected yet, 20 00:00:48.06 --> 00:00:51.03 as there are these two yellow warning symbols. 21 00:00:51.03 --> 00:00:52.09 So let's go ahead and fix that 22 00:00:52.09 --> 00:00:55.02 by first hitting the select button 23 00:00:55.02 --> 00:00:56.06 and selecting a room. 24 00:00:56.06 --> 00:00:59.04 For this example, let's select the lecture room. 25 00:00:59.04 --> 00:01:02.00 And then for the desk family instance, 26 00:01:02.00 --> 00:01:05.06 let's select this desk family just outside the building. 27 00:01:05.06 --> 00:01:08.04 Next we have the variable section. 28 00:01:08.04 --> 00:01:10.03 These are the values that change 29 00:01:10.03 --> 00:01:13.05 for the generative algorithm to generate different options. 30 00:01:13.05 --> 00:01:15.06 In our workspace layout study, 31 00:01:15.06 --> 00:01:18.04 the variables are the desk row rotation 32 00:01:18.04 --> 00:01:21.01 and the spacing between rows in feet. 33 00:01:21.01 --> 00:01:23.08 So the algorithm can test different variables 34 00:01:23.08 --> 00:01:26.00 to generate different desk layouts 35 00:01:26.00 --> 00:01:28.09 using these variables within these ranges, 36 00:01:28.09 --> 00:01:33.04 negative 90 to 90 and between 10 and 16 feet. 37 00:01:33.04 --> 00:01:35.09 These ranges are defined in the Dynamo graph 38 00:01:35.09 --> 00:01:37.07 that produced this study type, 39 00:01:37.07 --> 00:01:39.05 so we can't adjust them here. 40 00:01:39.05 --> 00:01:42.04 However, we can adjust how the algorithm tests 41 00:01:42.04 --> 00:01:45.04 these variables in both the Cross Product 42 00:01:45.04 --> 00:01:48.08 and the Like This method. 43 00:01:48.08 --> 00:01:50.05 In the Cross Product method, 44 00:01:50.05 --> 00:01:52.09 we can define how many values are used 45 00:01:52.09 --> 00:01:55.06 at intervals between these ranges. 46 00:01:55.06 --> 00:01:57.04 So here we have five, 47 00:01:57.04 --> 00:01:59.07 and so we'll test five different values 48 00:01:59.07 --> 00:02:01.06 between these two numbers. 49 00:02:01.06 --> 00:02:05.01 The same goes for the spacing between rows. 50 00:02:05.01 --> 00:02:07.09 And with the Like This method, 51 00:02:07.09 --> 00:02:10.08 we can set whereabouts in that range we'll want 52 00:02:10.08 --> 00:02:12.07 the algorithm to focus. 53 00:02:12.07 --> 00:02:14.08 Back to the Optimize method, 54 00:02:14.08 --> 00:02:19.03 the next section is the goals that we want to set. 55 00:02:19.03 --> 00:02:22.03 This input is unique to the Optimize method 56 00:02:22.03 --> 00:02:26.05 and determines what the objectives are for the optimization. 57 00:02:26.05 --> 00:02:29.01 This can be either minimized or maximized 58 00:02:29.01 --> 00:02:30.06 for each of the goals. 59 00:02:30.06 --> 00:02:33.09 Minimized understandably instructs the algorithm 60 00:02:33.09 --> 00:02:37.00 to try and reduce a value with each iteration 61 00:02:37.00 --> 00:02:38.08 of design solutions. 62 00:02:38.08 --> 00:02:41.02 So in this example, it will try to reduce 63 00:02:41.02 --> 00:02:43.06 the average distance to exits, 64 00:02:43.06 --> 00:02:47.00 meaning options generated with lower average distance 65 00:02:47.00 --> 00:02:50.02 to exits will be scored as a better option 66 00:02:50.02 --> 00:02:52.03 then the alternative. 67 00:02:52.03 --> 00:02:55.05 Maximize tells the algorithm to value options 68 00:02:55.05 --> 00:02:57.07 with higher values for these goals. 69 00:02:57.07 --> 00:03:00.06 So options with more views to the outside 70 00:03:00.06 --> 00:03:02.00 will be valued higher. 71 00:03:02.00 --> 00:03:05.04 For each option generated, an average score is determined 72 00:03:05.04 --> 00:03:07.01 based on all of the goals, 73 00:03:07.01 --> 00:03:09.02 which results in a final score. 74 00:03:09.02 --> 00:03:12.02 For this example, let's leave this at minimizing 75 00:03:12.02 --> 00:03:14.02 the average distance to exits, 76 00:03:14.02 --> 00:03:16.05 maximizing the views to outside, 77 00:03:16.05 --> 00:03:19.06 and maximizing the number of desks. 78 00:03:19.06 --> 00:03:23.00 Next, we have the constraints and constants. 79 00:03:23.00 --> 00:03:26.01 Constraints allows to set conditions for the algorithm 80 00:03:26.01 --> 00:03:29.01 to produce design options only if they are within 81 00:03:29.01 --> 00:03:30.09 an acceptable bound. 82 00:03:30.09 --> 00:03:34.03 For example, we could set the average distance to exits 83 00:03:34.03 --> 00:03:39.02 to be a minimum of three and a maximum of 15 84 00:03:39.02 --> 00:03:43.05 by selecting this checkbox over at the left of the input. 85 00:03:43.05 --> 00:03:46.00 Any options now produced by the algorithm 86 00:03:46.00 --> 00:03:47.08 that contain desks outside 87 00:03:47.08 --> 00:03:51.01 of these ranges will be discarded. 88 00:03:51.01 --> 00:03:53.04 Constants are similar, however rather 89 00:03:53.04 --> 00:03:57.03 than an acceptable range, we simply put a single number. 90 00:03:57.03 --> 00:03:58.08 We do this by setting the min 91 00:03:58.08 --> 00:04:00.09 and max as the same number. 92 00:04:00.09 --> 00:04:04.01 So for example, we could restrict the number of desks 93 00:04:04.01 --> 00:04:07.02 to be between 15 94 00:04:07.02 --> 00:04:10.02 and 15, which would mean that only options 95 00:04:10.02 --> 00:04:13.03 that have 15 desks would be shown to us. 96 00:04:13.03 --> 00:04:15.03 However, let's leave this off for the moment 97 00:04:15.03 --> 00:04:16.09 by unchecking it. 98 00:04:16.09 --> 00:04:18.08 All of these inputs will have an impact 99 00:04:18.08 --> 00:04:21.05 on how the Generative Design study runs 100 00:04:21.05 --> 00:04:23.07 and the results that it outputs. 101 00:04:23.07 --> 00:04:25.06 It's important to understand the impacts 102 00:04:25.06 --> 00:04:28.05 that these will have when running our studies. 103 00:04:28.05 --> 00:04:30.06 Once you have tweaked these how you like though, 104 00:04:30.06 --> 00:04:32.08 it's time to start generating results. 8244