I am developing a Windows Phone 7 app and I want to see how fast the user is going.
Right now, I am storing the last 2 locations (and timestamps) that were recorded. I am finding the distance between the 2 locations by using the method suggested here. Then I am finding the difference in time (timestamp2 - timestamp1) and calculating the speed using the formula speed = (distance/time).
Am I using the right method or should I use the GeoCoordinate.Speed property?
I don't see why shouldn't you just use the GeoCoordinate.Speed property!
The GeoCoordinate class already gives you the speed and course (heading) of the movement, so why not just use it?
Related
I’m making a game with GameMaker 1.4 and I’m in a dungeon room and I want to add drop sounds (like it’s damp) randomly.
Thank You!
Depending on how often you want the raindrop sound to play, you can use the random_range() function (https://docs.yoyogames.com/source/dadiospice/002_reference/maths/real%20valued%20functions/random_range.html) to variably count up to a pre-defined variable amount, or if it hits a specific number (like rolling a 1 through 4 on a 10 sided dice). Once that amount is hit, either randomly or by adding up to a threshold amount, you can just play the raindrop soundfile you have normally by using the audio_play_sound() function (https://docs.yoyogames.com/source/dadiospice/002_reference/game%20assets/sounds/audio_play_sound.html)
I am new to OctaPlanner.
I want to build a solution where I will nave number of locations to deliver items from one single location and also I want to use openmap distance data for calculating the distance.
Initially I used jsprit, but for more than 300 deliveries, it takes more than 8 minutes with 20 threads. Thats why I am trying to use Octa planner.
I want to map 1000 deliveries within 1 minute.
Does any one know any reference code or reference material which I can start using?
Thanks in advance :)
CVRPTW is a standard example, just open the examples app, vehicle routing and then import one of the belgium datasets with timewindows. The code is in the zip too.
To scale to 1k deliveries and especially beyond, you'll want to use "Nearby selection" (see reference manual), which isn't on by default but which makes a huge difference.
first post here because I've got a problem thats got me stumped. I am creating a calculation tool for a project at uni, now I'm not in an it degree but for this project I havent had problem too difficult until now.
Basically I am doing design work for a building, where each floor of the building can be allocated one of 9 possible designs. By then allocating solutions to each of these then calculating costs I am trying to find the most efficient combination.
Normally I would just use some nested loops to find the best design, no problems, but for the calculation tool I am required to change the number of floors, and therefore the number of nested loops, which I am unfamiliar with how to do.
The General structure is this
1- X Number of Floors.
9 Possible designs for each floor.
Based on each combination a cost must be calculated, and if it is within the best 5 results it will be stored.
There is a total of 9^x total solutions.
So
Floor = 1
For Solution = 1 to 9
Floor = 2
For Solution = 1 to 9
CalculateCost()
if CalculateCost < Best Then
Write, Floor1 Solution Value, Floor2 Solution Value to Output
Etc...
Now I am using Vb.net, and do not really know how to do recursion. If someone could simply point me in the way of a resource that may help me on this issue I would be very grateful.
Edit - Whilst I have tried to simplify, the cost of design implementation changes based on various other factors, so I can't simply just take the cheapest design for all. I have tried to solve this through practical theory and so far found so solution, therefore the brute force method is required
You're already using For loops to try each solution for each given floor, but you're manually iterating through your Floor variable. It seems you have 9 independently declared variables with the schema FloorX Solution Value. Given all of these things, I think what you really need is a dynamic array. Here's some rough code using this approach:
Dim FloorSolutionValues() As Byte ' I'm assuming values of 1-9
Dim NumberOfFloors As Integer ' Get this from the user
ReDim FloorSolutionValues(NumberOfFloors - 1)
For CurrentFloor As Integer = 0 To NumberOfFloors - 1
For CurrentSolution As Byte = 1 To 9
If CalculateCost() < FloorSolutionValues(CurrentFloor) Then
FloorSolutionValues(CurrentFloor) = CurrentSolution
End If
Next
Next
I'm making some assumptions that may or may not be true, but this should get you on the right path.
Y
I have 6 parameters for which I know maxi and mini values. I have a complex function that includes the 6 parameters and return a 7th value (say Y). I say complex because Y is not directly related to the 6 parameters; there are many embeded functions in between.
I would like to find the combination of the 6 parameters which returns the highest Y value. I first tried to calculate Y for every combination by constructing an hypercube but I have not enough memory in my computer. So I am looking for kinds of markov chains which progress in the delimited parameter space, and are able to overpass local peaks.
when I give one combination of the 6 parameters, I would like to know the highest local Y value. I tried to write a code with an iterative chain like a markov's one, but I am not sure how to process when the chain reach an edge of the parameter space. Obviously, some algorythms should already exist for this.
Question: Does anybody know what are the best functions in R to do these two things? I read that optim() could be appropriate to find the global peak but I am not sure that it can deal with complex functions (I prefer asking before engaging in a long (for me) process of code writing). And fot he local peaks? optim() should not be able to do this
In advance, thank you for any lead
Julien from France
Take a look at the Optimization and Mathematical Programming Task View on CRAN. I've personally found the differential evolution algorithm to be very fast and robust. It's implemented in the DEoptim package. The rgenoud package is another good candidate.
I like to use the Metropolis-Hastings algorithm. Since you are limiting each parameter to a range, the simple thing to do is let your proposal distribution simply be uniform over the range. That way, you won't run off the edges. It won't be fast, but if you let it run long enough, it will do a good job of sampling your space. The samples will congregate at each peak, and will spread out around them in a way that reflects the local curvature.
I am using VB.NET and I am trying to come up with some algorithm or some pseudo-code, or some VB.NET code that will let me do the following (hopefully I can explain this well):
I have 2 collection objects, Cob1 and Cob2. These collection objects store objects that implement an interface called ICob. ICob has 3 properties. A boolean IsSelected property, a property called Length, which returns a TimeSpan, and a Rating property, which is a short integer.
OK, now Cob1 has about 100 objects stored in the collection and Cob2 is an empty collection. What I want to do is select objects from Cob1 and copy them over to Cob2. I want the following rules obeyed when selecting the objects though:
I want to be able to specify a timespan and I want enough objects to be selected to fit into the timespan I specify (based on the Length property). So for example, if I pass a 10 minute timespan to my function, it should pick enough objects that fill the entire 10 minute window, or come as close to filling it as possible.
No objects should be selected twice.
Objects that have a higher rating (via the Rating property) should have a better chance at being picked then other objects.
No object that has been selected in the last 30 minutes should be selected again (so that each object will eventually get selected at least once), regardless of rating.
Can anyone give me some tips on how to achieve this? The tips can be in the form of mental processes, VB.NET example code, Pseudo-code or just about anything else that might help me.
Thanks
EDIT:
Maybe It would help to everyone if I revealed what I'm trying to do in real life.
I am writing software for a radio station that will automatically select the music and advertisments to play, kinda of like a computerized program manager.
The length represents the length of the sound byte (either a song or an advertisement) and the rating is just that. If the song is popular, it gets more airtime. If an advertiser pays more money, then it also gets more airtime.
So my program should pick songs that play for 20 minutes or so, then pick some advertisements to play for about 5 minutes or so.
Hopefully this helps a little.
Thanks for the input from everyone!
Alan
Note that:
The restriction 1 is from the classical knapsack problem, which works on sets, as requested by restriction 2.
Restriction 3 is rather vague. It is better to have higher value or higher coverage of the lifespan? If you don't specify a objective function to maximaze (or, to be precise, there are two: lifespan itself and rate), there are some pareto optimal solutions.
Restriction 4 is implementable by making a map object -> last time selected., in the form of black list.
Long story short: first I'd filter the set by blacklisting the object by restriction 4, and then apply a knapsack algorithm.
In order to implement 4., I believe you'll need to save the date/time when the Cob was last selected. Then, I'd do it in the following steps:
Filter out the ones that have not been selected within the last 30 minutes.
Sort by rating and set your "cursor" on the first item in the list.
Check the item's timespan. If short enough to fit in the specified time, select it. If not, goto 3 and proceed with the next item.
Check if your timespan has been filled. If yes, you are done. If no, goto 3 and proceed with the next item.