Abstract
Scheduling consists mainly of allocating resources to jobs over time under necessary constraints. In the past, the processing time for each job was usually assigned or estimated as a fixed value. In many real-world applications, however, job processing time may vary dynamically with the situation. In this paper, fuzzy concepts are applied to Johnson algorithm for managing uncertain scheduling. Given a set of jobs, each having two tasks that must be executed on two machines, and their processing time membership functions, the fuzzy Johnson algorithm can yield a scheduling result with a membership function for the final completion time, thus helping managers gain a broader overall view of scheduling. Also, the conventional Johnson algorithm is shown as a special case of the fuzzy Johnson algorithm with special membership functions being assigned. The fuzzy Johnson algorithm is thus a feasible solution for both deterministic and uncertain scheduling.
Get full access to this article
View all access options for this article.