A neural network algorithm for servicing jobs with sequential and parallel machines
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We consider the FJ‖C max problem of optimal servicing with respect to performance for a given set of jobs by sequential and parallel machines. The problem FJ‖C max is a generalization of the classical J‖C max problem for the case when the servicing system has not only sequential but also parallel (identical) machines. We propose a two-stage algorithm for a heuristic solution of problem FJ‖C max On the first stage, we solve the problem J‖C max, i.e., we assume that the servicing system does not have parallel machines. On the second stage, operations are distributed over parallel machines. On both stages of the algorithm, we use neural network decision making models. The efficiency of a neural network algorithm for the problem J‖C max and problem FJ‖C max was evaluated on 20 test examples obtained from 20 known J‖C max problems by including into the servicing system a random number of copies of sequential machines.
KeywordsSchedule Problem Remote Control Parallel Machine Priority Rule Heuristic Solution
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