
Covering the Aztec Diamond
... the union of unit squares in the plane whose centers are contained in the equation |x| + |y| ≤ n [3]: ...
... the union of unit squares in the plane whose centers are contained in the equation |x| + |y| ≤ n [3]: ...
CHAPTER 3
... Give a set S of n numbers,there is a number p which divides S into three subsets S1,S2and S3. case1:the size of S is greater than k.Kth smallest of S must be located in S1 ,prune away S2 and S3. case2:the condition of Case1 is not valid.But the size of S1 and S2 is greater than k.the kth smallest nu ...
... Give a set S of n numbers,there is a number p which divides S into three subsets S1,S2and S3. case1:the size of S is greater than k.Kth smallest of S must be located in S1 ,prune away S2 and S3. case2:the condition of Case1 is not valid.But the size of S1 and S2 is greater than k.the kth smallest nu ...
File
... In addition to the Sumerian irrigation system, how else did they control the water supply? ...
... In addition to the Sumerian irrigation system, how else did they control the water supply? ...
Sequence Assembly
... SBH Problem • Given: A set S of k-mers • Do: Find a string s, such that spectrum(s,k) = S ...
... SBH Problem • Given: A set S of k-mers • Do: Find a string s, such that spectrum(s,k) = S ...
Given any resolution rule, a planar straight line upward drawing of
... the extremal endpoints to the shaft gives the number of edges in the shaft making its construction unique as well ...
... the extremal endpoints to the shaft gives the number of edges in the shaft making its construction unique as well ...
Solutions to Assignment 2.
... half the input at each step. Note that finding the median in a sorted array A of length n is O(1), since the median is just A[n/2]. So let x1 = X[n/2] and y1 = Y [n/2], and let m be the median value we’re looking for. There are four possible locations for m: X[1, . . . , n2 ], X[ n2 , . . . , n], Y ...
... half the input at each step. Note that finding the median in a sorted array A of length n is O(1), since the median is just A[n/2]. So let x1 = X[n/2] and y1 = Y [n/2], and let m be the median value we’re looking for. There are four possible locations for m: X[1, . . . , n2 ], X[ n2 , . . . , n], Y ...
IntroToAI_2_2_2012
... An optimization algorithm is an algorithm which takes as input a solution space, an objective function which maps each point in the solution space to a linearly ordered set, and a desired goal element in the set. ...
... An optimization algorithm is an algorithm which takes as input a solution space, an objective function which maps each point in the solution space to a linearly ordered set, and a desired goal element in the set. ...
Travelling salesman problem
The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.TSP is a special case of the travelling purchaser problem and the Vehicle routing problem.In the theory of computational complexity, the decision version of the TSP (where, given a length L, the task is to decide whether the graph has any tour shorter than L) belongs to the class of NP-complete problems. Thus, it is possible that the worst-case running time for any algorithm for the TSP increases superpolynomially (perhaps, specifically, exponentially) with the number of cities.The problem was first formulated in 1930 and is one of the most intensively studied problems in optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally difficult, a large number of heuristics and exact methods are known, so that some instances with tens of thousands of cities can be solved completely and even problems with millions of cities can be approximated within a small fraction of 1%.The TSP has several applications even in its purest formulation, such as planning, logistics, and the manufacture of microchips. Slightly modified, it appears as a sub-problem in many areas, such as DNA sequencing. In these applications, the concept city represents, for example, customers, soldering points, or DNA fragments, and the concept distance represents travelling times or cost, or a similarity measure between DNA fragments. The TSP also appears in astronomy, as astronomers observing many sources will want to minimise the time spent slewing the telescope between the sources. In many applications, additional constraints such as limited resources or time windows may be imposed.