When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. k shortest path routing - Wikipedia

    en.wikipedia.org/wiki/K_shortest_path_routing

    A solution was given by B. L. Fox in 1975 in which the k-shortest paths are determined in O(m + kn log n) asymptotic time complexity (using big O notation. [5] In 1998, David Eppstein reported an approach that maintains an asymptotic complexity of O ( m + n log n + k ) by computing an implicit representation of the paths, each of which can be ...

  3. Access time - Wikipedia

    en.wikipedia.org/wiki/Access_time

    Access time is the time delay or latency between a request to an electronic system, and the access being initiated or the requested data returned.. In computer and software systems, it is the time interval between the point where an instruction control unit initiates a call to retrieve data or a request to store data, and the point at which delivery of the data is completed or the storage is ...

  4. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a ...

  5. k-server problem - Wikipedia

    en.wikipedia.org/wiki/K-server_problem

    This conjecture states that there is an algorithm for solving the k-server problem in an arbitrary metric space and for any number k of servers that has competitive ratio exactly k. Manasse et al. were able to prove their conjecture when k = 2, and for more general values of k for some metric spaces restricted to have exactly k+1 points.

  6. Computational complexity - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity

    As the amount of resources required to run an algorithm generally varies with the size of the input, the complexity is typically expressed as a function n → f(n), where n is the size of the input and f(n) is either the worst-case complexity (the maximum of the amount of resources that are needed over all inputs of size n) or the average-case ...

  7. How To Turn $100K Into A Million: Your Step-By-Step Guide - AOL

    www.aol.com/finance/invested-100k-turned-1...

    The first step in turning $100K into $1 million is to gauge whether or not you have $100K as a reasonable starting point. This amount should be free and clear of any major debts or taxes you owe.

  8. Debt consolidation vs. debt payoff vs. debt counseling: What ...

    www.aol.com/debt-consolidation-vs-debt-payoff-vs...

    You have stable income to repay your loan on time Case study: Debt consolidation for $25,000 in credit card debt Joanne has $25,000 spread across four credit cards with interest rates between 18% ...

  9. Worst-case complexity - Wikipedia

    en.wikipedia.org/wiki/Worst-case_complexity

    It gives an upper bound on the resources required by the algorithm. In the case of running time, the worst-case time complexity indicates the longest running time performed by an algorithm given any input of size n , and thus guarantees that the algorithm will finish in the indicated period of time.