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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 ...
Flow Shop Scheduling Problem; Generalized assignment problem; Integer programming. The variant where variables are required to be 0 or 1, called zero-one linear programming, and several other variants are also NP-complete [2] [3]: MP1 Some problems related to Job-shop scheduling
The list scheduling algorithm by Garey and Graham [9] has an absolute ratio , as pointed out by Turek et al. [10] and Ludwig and Tiwari. [11] Feldmann, Sgall and Teng [ 12 ] observed that the length of a non-preemptive schedule produced by the list scheduling algorithm is actually at most ( 2 − 1 / m ) {\displaystyle (2-1/m)} times the ...
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.
The algorithms used in scheduling analysis “can be classified as pre-emptive or non-pre-emptive". [1] A scheduling algorithm defines how tasks are processed by the scheduling system. In general terms, in the algorithm for a real-time scheduling system, each task is assigned a description, deadline and an identifier (indicating priority).
Many exact and approximation algorithms are known. Graham proved that: Any list scheduling algorithm (an algorithm that processes the jobs in an arbitrary fixed order, and schedules each job to the first available machine) is a / approximation for identical machines. [3] The bound is tight for any m.
Single-machine scheduling or single-resource scheduling is an optimization problem in computer science and operations research. We are given n jobs J 1 , J 2 , ..., J n of varying processing times, which need to be scheduled on a single machine, in a way that optimizes a certain objective, such as the throughput .
The modified due date scheduling is a scheduling heuristic created in 1982 by Baker and Bertrand, [1] used to solve the NP-hard single machine total-weighted tardiness problem. This problem is centered around reducing the global tardiness of a list of tasks which are characterized by their processing time, due date and weight by re-ordering them.