-Stochastic Scheduling Flow-Shop No-Wait with Heuristics Using Artificial Intelligence Techniques
This paper treats Scheduling models that can be described by considering in sequence the resources, tasks systems, sequencing constraints and performance measures. The conditions Flow-shop means that the tasks of each job should be processing sequentially, there is one machine for each task, a job is processed using one machine at a time without preemption and a machine process exactly one job at a time. The condition No-wait means that delays between tasks of the same job are not allowed. In this particular case, Flow-shop No-wait, the schedule is determined by a sequence of jobs. The Stochastic hypothesis is that: the processing times of the job i on machine j are random, according to some continuous and independent distribution functions T ij and with the realizations known only during the shop. The Objective is to minimize the expected value of the makespan, where the makespan, cmax, is the total amount of time required to completely process all the jobs [Coffman 1976, Ferreira 1990, Frostig 1985].
Unable to display preview. Download preview PDF.
- Coffman Jr, E.G. (1976). Computer and lob-Shop Scheduling Theory. New York, John Wiley.Google Scholar
- Ferreira, U. (1990). Stochastic Scheduling Flow-shop No-wait Problems. ITA, São José dos Campos, SP, 1990. Tese de Doutorado.Google Scholar
- Goldberg, D. (1989). Genetic Algorithms in Search. Optimization and Machine Learning. Addison-Wesley.Google Scholar
- Hertz J.; Krogh, A & Palmer, R G. (1991). Introduction to the Theory of Neural Computation. Addison Wesley.Google Scholar