A Genetic Algorithm-Based Advanced Planning and Scheduling Method for Multi-Resource Parallel Tasks

Abstract

The present invention provides a genetic algorithm-based multi-resource parallel task advanced planning and scheduling method, which takes the genetic algorithm as the core, and is based on the dynamic determination of the process path and the dynamic generation of the manufacturing capacity. This method utilizes multi-resource combination constraints, adjacency matrix construction and analysis, and efficient iteration of genetic algorithms to achieve flexible matching of enterprise resource requirements, automatic sorting of process paths, and automatic scheduling of multiple order tasks. The present invention realizes a method of accurately outputting the process paths of different products into the operation rules with a common operation logic. When the product process path is changed, the corresponding process execution sequence can be output without changing the program code. , thereby improving the universality and efficiency of scheduling results.

Description

technical field [0001] The invention relates to the field of advanced planning and scheduling, in particular to a method for advanced planning and scheduling of multi-resource parallel tasks based on genetic algorithm. Background technique [0002] With the popularization of computer technology, the production mode of enterprises is gradually changing, and it is changing from traditional manufacturing methods to intelligent ones. However, the production planning and scheduling of most manufacturing enterprises is still manually arranged by the planners using computer tools, mainly to roughly divide the tasks into procedures and schedule the divided procedures. Depending on the experience level of the planners, it is impossible to realize the efficient transfer of people, machines, materials, methods, and rings in the process. [0003] With the continuous development of informatization, big data, digitalization and intelligence, the emergence of Advanced Planning and Schedul...

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Problems solved by technology

[0004] However, the current mainstream APS method is based on the situation of fixed production line manufacturing capacity, determined process path, and single resource demand. It uses mathematical programming, heuristic algorithms, and intelligent optimization algorithms to achieve task allocation. It can only cover core or Bottleneck resource calculation, it is difficult to perform comprehensive calculation of multiple resource elements (personnel, time, equipment, workstations)

For complex equipment manufacturing enterprises with multiple varieties and small batch types, the current mainstream advanced planning and scheduling methods are not universal in view of their characteristics such as complex and changeable process paths, large order volumes, many types of resource requirements, and frequent business changes.

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