Sequencing to minimize mean finishing time (or mean time in system) is not only desirable to the user, but it also tends to minimize at each point in time the storage required to hold incomplete tasks. In this paper a deterministic model of independent tasks is introduced and new results are derived which extend and generalize the algorithms known for minimizing mean finishing time. In addition to presenting and analyzing new algorithms it is shown that the most general mean-finishing-time problem for independent tasks is polynomial complete, and hence unlikely to admit of a non-enumerative solution.
A method for assigning tasks or resources, based on a model of division of labor in social insects, is introduced and applied to a dynamic flow shop scheduling problem. The prob...
In order to exploit fully a fast computer which possesses simultaneous processing abilities, it should to a large extent schedule its own workload. The scheduling routine must b...
The aim of this paper is to evaluate the performance of genetic algorithms for the flowshop scheduling problem with an objective of minimizing the makespan. First we examine var...
Written for specialists working in optimization, mathematical programming, or control theory. The general theory of path-following and potential reduction interior point polynom...
A model for multiprocessor control is considered in which jobs are broken into various pieces, called tasks . Tasks are executed by single processing units. In this paper the st...
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