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Parallel machine scheduling case study

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The minimum makespan of parallel machine scheduling is studied when the processing times are random variables. Using a connection to empirical processes our approach aims at a deep insight into the asymptotic behavior of the minimum makespan. We will give an analytical expression for the constant c that is important, it enables us for instance to calculate the constant for unrelated machines and uniformly distributed processing times. Furthermore the analysis gives strong results such as a rate of convergence, an exponential in equality of the tail probability of the difference between the minimum makespan and cn and a central limit theorem.

Parallel Job Scheduling Policies to Improve Fairness: A Case Study

Parallel Machine Shop Scheduling Using Memetic Algorithm |

Simulated Annealing - Advances, Applications and Hybridizations. This chapter presents the problem of scheduling tasks in uniform parallel machines with sequence-dependent setup times. The problem under analysis has a particular set of constraints, including equipment capacity, precedence tasks, lot sizing and task delivery plan. This kind of problem should be considered an operational planning problem and is found in different types of industries, namely, in the textile industry. The main goal of this work is to minimise the total production time, including processing, setup and tardiness time. The complexity of the studied model does not allow to locate the optimal solution.


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Parallel machine shop scheduling problem can be stated as finding a schedule for a general task graph to execute on a customed flow so that the schedule length can be minimized. Parallel Flow Shop Scheduling with a case study has been. In this study we present an effective memetic algorithm to solve the problem.

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