Parallel machine group scheduling method and system based on improved artificial immune algorithm

Abstract

An embodiment of the invention relates to a parallel machine group scheduling method and a parallel machine group scheduling system based on an improved artificial immune algorithm. The parallel machine group scheduling method comprises the steps of: 1, setting algorithm parameters; 2, randomly generating an initial solution; 3, calculating a fitness value and determining a global optimal solution; 4, calculating an antibody concentration; 5, calculating a selection probability of each individual; 6, carrying out crossover and mutation; 7, conducting variable neighborhood search; 8, updating populations; 9, and determining whether a termination condition is satisfied, if so, outputting the global optimal solution, otherwise, returning to the step 3. The parallel machine group scheduling method and the parallel machine group scheduling system can solve the parallel machine group scheduling problem under the deteriorating workpiece condition, and obtain an approximate optimal solution; and a solution model is closer to the actual production process, thereby being conductive to improving the production efficiency and optimizing the service quality of an enterprises in a complex production environment.

Description

technical field [0001] The embodiment of the present invention relates to the field of software technology, and in particular to a group scheduling method and system for parallel machines based on an improved artificial immune algorithm. Background technique [0002] Batch scheduling problems widely exist in all walks of life in modern processing and manufacturing, such as semiconductor manufacturing, cargo transportation, aviation industry, etc. Different from the classic scheduling problem in which a machine can only process one workpiece at the same time, a batch processor can process a batch of workpieces at the same time, which helps to improve production efficiency. In addition, in the production environment of multiple varieties and small batches, in order to shorten the processing time, enterprises can use group technology for mixed flow production, and the resulting scheduling problem is called group scheduling problem. The organic combination of batch scheduling a...

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Problems solved by technology

[0004] However, in the process of carrying out the invention, the inventors found that the prior art has the following defects: in previous studies, the research on batch scheduling mainly focused on single-machine and parallel machine problems; the research on group scheduling mainly focused on single-machine , Flow workshop problem

In addition, the demand for multi-variety and small-batch production also makes group scheduling actually exist in the processing process of parallel machine batch scheduling, which cannot be ignored

This type of batch scheduling problem is more complicated, it needs to consider many factors such as workpiece deterioration, group distribution on machines, group processing sequence, workpiece group batching method and workpiece processing sequence, etc.

In addition, in terms of method, the artificial immune algorithm also has shortcomings such as poor local convergence and premature maturity, and there are also problems in the process of calculating antibody affinity and antibody concentration based on information entropy

Unable to provide consistently stable and reliable solutions to specific scheduling problems

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