dynamic-programming

问题 I am trying to explore Apache commons configuration to dynamically load the property file and do modification in the file and save it. I wrote a demo code for the same. Code Snippet package ABC; import org.apache.commons.configuration.ConfigurationException; import org.apache.commons.configuration.PropertiesConfiguration; import org.apache.commons.configuration.reloading.FileChangedReloadingStrategy; public class Prop { public static void main(String[] args) { try { URL propertiesURL = Prop

问题 I'm solving this problem "Making change" in javascript: Question: Given an amount of money, an array of coin denominations, compute the number of ways to make the amount of money with coins of the available denominations. Example: For amount=4 (4¢) and denominations=[1,2,3] (1¢, 2¢ and 3¢), your program would output 4—the number of ways to make 4¢ with those denominations: 1¢, 1¢, 1¢, 1¢ 1¢, 1¢, 2¢ 1¢, 3¢ 2¢, 2¢ I found a solution: var makeChange = function(total){ var count = 0; var coins =

问题 I am about to take part in a dance contest and tomorrow is the big day! I know apriori the list with the n songs of the contest and their order. After much scouting, I was able to determine the judges and my skills so good that I can accurately predict my result if I dance the i-th song of the list, i.e. score(i) . However, after the i-th song, I need time to rest, namely I cannot dance the next rest(i) songs, i.e. songs i + 1, ..., i + rest(i). No other constraint exists for the number of

问题 We usually the following recurrence relation for the coin change problem: ( P is the total money for which we need change and d_i is the coin available) But can't we make it like this: ( V is the given sorted set of coins available, i and j are its subscripts with Vj being the highest value coin given) C[p,Vi,j] = C[p,Vi,j-1] if Vj > p = C[p-Vj,Vi,j] + 1 if Vj <=p Is there anything wrong with what I wrote? Though the solution is not dynamic but isn't it more efficient? 回答1: Consider P = 6, V

问题 I need help with the Pythonic looping overhead of the following problem: I'm writing a function that calculates a pixel flow algorithm that's a classic dynamic programming algorithm on a 2D Numpy array. It requires: 1) visiting all the elements of the array at least once like this: for x in range(xsize): for y in range(ysize): updateDistance(x,y) 2) potentially following a path of elements based on the values of the neighbors of an element which looks like this while len(workingList) > 0: x,y

问题 I am working on some task which requires from me to solve the following algorithmic problem: - You Have collection of items (their weights): [w1, w2, ..., wn] - And You have a bag which weight is: W - It is Needed to fill the bag maximally (fill as much as possible) with the subset of given items. So this is not "Knapsack 0/1" problem, as we deal only with weights (we have only one parameter for item). Therefore I assume that it might have a solution (Knapsack is NP-complete) or some kind of

问题 Word Break (with Dynamic Programming: Top->Down) Given a string s and a dictionary of words dict, add spaces in s to construct a sentence where each word is a valid dictionary word. Return all such possible sentences. For example , given s = "catsanddog", dict = ["cat", "cats", "and", "sand", "dog"]. A solution is ["cats and dog", "cat sand dog"]. Question: Time complexity ? Space complexity ? Personally I think, Time complexity = O(n!), without Dynamic Programming, n is the length of the

问题 I'm looking for an algorithm that addresses the LCS problem for two strings with the following conditions: Each string consists of English characters and each character has a weight. For example: sequence 1 (S1): "ABBCD" with weights [1, 2, 4, 1, 3] sequence 2 (S2): "TBDC" with weights [7, 5, 1, 2] Suppose that MW(s, S) is defined as the maximum weight of the sub-sequence s in string S with respect to the associated weights. The heaviest common sub-sequence (HCS) is defined as: HCS = argmin

问题 I wonder if the objective function of a general dynamic programming problem can always be formulated as in dynamic programming on wiki, where the objective function is a sum of items for action and state at every stage? Or that is just a specical case and what is the general formulation? EDIT: By "dynamic programming problem", I mean a problem that can be solved by dynamic programming technique. Such kind of problems possess the property of optimal problem and optimal structure. But at lease

问题 I'm not really good in maths, so I'm having really hard times converting formulas into code, and I can't find anything ready-made googling around. I have a big rectangle containing a lot of small rectangles... and all what I need to do is to calculate the largest empty rectangle. Anyonne can help me? Here is what I came up with... nothing to say, it's a big fail. Rect result = new Rect(); for (Double l = 0; l < bigRect.Width; ++l) { for (Double t = 0; t < bigRect.Height; ++t) { Double h = 0;