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Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).
Longest-processing-time-first (LPT) is a greedy algorithm for job scheduling. The input to the algorithm is a set of jobs, each of which has a specific processing-time. There is also a number m specifying the number of machines that can process the jobs. The LPT algorithm works as follows:
But in complex situations it can easily fail to find the optimal scheduling. HEFT is essentially a greedy algorithm and incapable of making short-term sacrifices for long term benefits. Some improved algorithms based on HEFT look ahead to better estimate the quality of a scheduling decision can be used to trade run-time for scheduling performance.
In computer science, greedy number partitioning is a class of greedy algorithms for multiway number partitioning. The input to the algorithm is a set S of numbers, and a parameter k. The required output is a partition of S into k subsets, such that the sums in the subsets are as nearly equal as possible. Greedy algorithms process the numbers ...
The Complete Greedy Algorithm (CGA) considers all partitions by constructing a k-ary tree. Each level in the tree corresponds to an input number, where the root corresponds to the largest number, the level below to the next-largest number, etc. Each of the k branches corresponds to a different set in which the current number can be put.
Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs (also called processes or tasks) and a list of machines (also called processors or workers). The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective ...
Otherwise, disregard the interval. The interval scheduling problem can be viewed as a profit maximization problem, where the number of intervals in the mutually compatible subset is the profit. The charging argument can be used to show that the earliest finish time algorithm is optimal for the interval scheduling problem.
The matching pursuit is an example of a greedy algorithm applied on signal approximation. A greedy algorithm finds the optimal solution to Malfatti's problem of finding three disjoint circles within a given triangle that maximize the total area of the circles; it is conjectured that the same greedy algorithm is optimal for any number of circles.