What bothers me the most is that late generations still seem to deviate much from the optimum value for objective 3 and 4 (which are the constraints the solution Ofcourse I have some personal interest in solving this problem, as well... my thesis sort of depends on solving it. And according to the following images simulation produced lots of repeated fitness values (in each fitness objective).This following image is an example that shows lots of solutions are actually overlapping. Traceback (most recent…Continue. To avoid any comments advicing me to use the Karamaba "optimize cross section" component, it won't serve the purpose of my research. To avoid any comments advicing me to use the Karamaba "optimize cross section" component, it won't serve the … I hope to obtain some valid results that way. Abstract. While this might sound similair in my opinion it is not. Hi Milad, Thank you for your reply, it will be great if you add resume and simulation by section. I am not looking to constrain a value in a range, I am looking to not have that value exceed a certain limit. Following your suggestion to limit the range even further untill only valid outputs are created means I will actually lose some valid outputs (such as the one displayed in the top figure). Exactly why I don’t know. In theory it is however exactly the answer I am looking for.
I'm sorry if this is a silly question; but as I was exporting solutions I realised I had made a mistake, so I hit the "Stop E…Hi, i'm working on optimization visual comfort with honeybee component Daylight simulation, Read annual result and Glare Analysis. 2: May 8 Reply by Akash Changlani p.s. I honestly wish I didn't allready try that as I am currently running out of options. As you can see in the second image, the outputted data from all the outputs in WallaceiX have the same data structure. I understand that my design space is very limited, however this was done intentionally as I was purely trying to prove the concept of evolutionary design on a very very simple test case.The results you have obtained was all I wanted to achieve with this problem! Previously, with SR11 it went well. I also tried to run it on 2 different computers. The script is setup accordingly (full definition included as attachment):Without including the constraints the solver will quickly converge towards the lowest possible height (2m) and the lowest possible cross section (IPE120) to maximize weight reduction.
I would say there are enough valid solutions for WallaceiX to work with (especially after the 1st method has limited the genome range).First of all, let me please react on the use of the word “range” as it does compromise what I am looking for. Hi, for my thesis I am looking into the subject of generative structural design. Could you maybe elaborate on this? Utilizing an evolutionary algorithm in design is comprising of three important parts each of which holds equal weight in this process.First and foremost is the formulation of the design problem. Any help or thoughts would be greatly appreciated :) ! Any help or thoughts would be greatly appreciated :) ! Therefore WallaceiX will again converge towards minimizing the two goals without understanding the connection between them.
Especially when problems become more complex I can image it reduces the run time of the simulation.
Sort by: Hi, I will be using this to check if I have obtained valid solutions and filter out any non-valid solutions. !Any Id…Hi! No matter how large I set my population. You can create a condition which evaluates whether these values are within the range or not and use this condition to replace one of your objectives with an empty value before connecting it to WallaceiX. By looking at your grasshopper definition I can say that this may not be the best way to move forward because it is quite hard to find the right domain in your genes and sliders in the first look.2-You can record the “deflection values” and “Utilization rate” for each individual in the entire simulation and then when simulation finished you can simply select the solutions in which these two values are within your desired range. This means that simulation will try to reduce this value, it means that deflection values are getting closer and closer to 12 (or will be in a specified domain). So, if you record these two constraints/values, when simulation finishes you can simply use the Data output of WallaceiX to choose the ones that are in the domain and use the same true/false pattern to cull/select the correct individuals. Not a single valid result obtained so far.Do you perhaps remember the exact WallaceiX setup you ran the simulation with? I would like to give my feedback on the obtained results using the four methods you described. Does anyone knows what is 'n' in the Mutation Probability 1/n within optimisation interface 'Walacei Settings'? However, you must agree that it does not tackle the core of the problem as some combinations of genomes will still result in design variants being created which do not meet the constraints.Example (see figure): The range of “bottom chord and top chord” have been reduced by finding the minimum allowable when the other criteria (height in this case) is maximized. ?Hello, Wallacei Phenotypes: WPhenotypes: Insert the Wphenotypes from the WallaceiX component; Do not simplify the tree in order to take full advantage of data structure: Goo: Size of the grid in the x direction: Size X: Insert a number to define the size of the grid in the x direction: Number: Size of the grid in the y … Thank you for your question and a clear explanation of the problem.There are multiple ways to address the “constraint” while using WallaceiX. But from an engineering point of view I think implementing constraints, boundary conditions, limits, (whatever you want to call it) is of great importance!By sharing my results I hope to continue this discussion and work towards a solution with the gh commnity. Your explanation about correctly setting up an evolutionary design problem is much appreciated. But Why? This means By studying your design problem one thing caught my eyes the most. These solutions are spread over the entire population, from the first generations to the last.About the weighting factors, We are working on it to implement it in the future releases.Hope Wallacei would be helpful for you and good luck with your research and thesis.Thank you once again for your detailed answer. I want to define a domain for my result, (for example i want result which are in domain.0.3 and.0.9)
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