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Performance Guarantees for Scheduling Algorithms
Operations Research, 1978One approach to coping with the apparent difficulty of many schedule-optimization problems, such as occur in machine shops and computer processing, is to devise efficient algorithms that find schedules guaranteed to be “near-optimal.” This paper presents an introduction to this approach by describing its application to a well-known multiprocessor ...
M. R. Garey +2 more
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Stability and distributed scheduling algorithms
Proceedings of the 1985 ACM thirteenth annual conference on Computer Science - CSC '85, 1985Many distributed scheduling algorithms have been developed and reported in the current literature. However, very few of them explicitly treat stability issues. This paper first discusses stability issues for distributed scheduling algorithms in general terms.
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A Level Algorithm for Preemptive Scheduling
Journal of the ACM, 1977Muntz and Coffman give a level algorithm that constructs optimal preemptive schedules on identical processors when the task system is a tree or when there are only two processors available. Their algorithm is adapted here to handle processors of different speeds.
Edward C. Horvath, Shui Lam, Ravi Sethi
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Design of Scheduling Algorithms: Applications
2010This chapter discusses the insights developed for designing scheduling algorithms according to three design projects where algorithms have been developed. The choice of applications covers a broad spectrum. The methods used are from three different fields, namely combinatorial optimization, genetic (evolutionary) algorithms, and mathematical ...
Jan, Riezebos +5 more
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Algorithms for Scheduling Independent Tasks
Journal of the ACM, 1976The following job sequencing problems are studied: (i) single processor job sequencing with deadlines, (ii) job sequencing on m -identical processors to minimize finish time and related problems, (iii) job sequencing on 2-identical processors to minimize weighted mean flow time.
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Genetic Algorithms for Scheduling Examinations
2021The range of problems to which genetic algorithms have been applied is quite broad. Timetable scheduling is a complex optimization problem. The purpose is to solve this problem by using genetic algorithms. There are two implementations for this problem: the first one solves the complete issue, and the second one divides the problem into two phases and ...
Farshid Hajati +2 more
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An Optimal Drum Scheduling Algorithm
IEEE Transactions on Computers, 1972Suppose a set of N records must be read or written from a drum, fixed-head disk, or similar storage unit of a computer system. The records vary in length and are arbitrarily located on the surface of the drum. The problem considered here is to find an algorithm that schedules the processing of these records with the minimal total amount of rotational ...
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ACM Transactions on Algorithms, 2011
Broadcast Scheduling is a popular method for disseminating information in response to client requests. There are n pages of information, and clients request pages at different times. However, multiple clients can have their requests satisfied by a single broadcast of the requested page.
Jessica Chang +3 more
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Broadcast Scheduling is a popular method for disseminating information in response to client requests. There are n pages of information, and clients request pages at different times. However, multiple clients can have their requests satisfied by a single broadcast of the requested page.
Jessica Chang +3 more
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Scheduled-Stepsize NLMS Algorithm
IEEE Signal Processing Letters, 2009This paper presents a method of scheduling stepsizes for the normalized least-mean-squares (SS-NLMS) algorithm. Geometrically interpreting the mean square deviation (MSD) learning curve leads to establishing an objective curve and to constructing a lookup table of stepsizes in order for the MSD to follow the curve.
PooGyeon Park +2 more
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Production scheduling and genetic algorithms
1995This treatise deals with the applicability of genetic algorithms to the area of production scheduling. To begin with, an introduction to the principles of genetic algorithms is given. After having outlined a standard genetic algorithm, first approaches to the traveling salesman problem are explained.
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