Improved unified particle swarm algorithm-based mechanical part machining pipeline scheduling method

Abstract

The invention discloses a mechanical part machining pipeline scheduling method of employing a dynamic neighborhood and comprehensive learning-based discrete unified particle swarm algorithm. The mechanical part machining pipeline scheduling method comprises the following steps of reading operation time of mechanical part machining; carrying out population initialization; calculating a fitness value of each particle and sorting the particles; updating an optimal position, an individual optimal position, a global optimal position and a learning item in each particle neighborhood; carrying out global searching by adopting dynamic neighborhood and comprehensive learning-based discrete unified particle swarm optimization; carrying out elite learning strategy-based local searching; regrouping populations after a certain number of times; and recombining the learning items when updating of a global optimal solution stalls. According to the mechanical part machining pipeline scheduling method,the limitation of the dynamic neighborhood and comprehensive learning-based unified particle swarm optimization in the field of production scheduling is improved; the defects that standard particle swarm optimization depends too much on parameters and is easy to fall into local optimum are overcome; the mechanical part machining pipeline scheduling method has the characteristics of high search accuracy, a high convergence rate and the like; and furthermore, the mechanical part machining pipeline scheduling method is relatively wide in application range and can be extended to the fields of manufacturing and process industries.

Description

technical field [0001] The invention relates to a pipeline scheduling method for machining mechanical parts, in particular to a pipeline scheduling method for machining mechanical parts based on a discrete unified particle swarm algorithm based on dynamic neighborhood and comprehensive learning. Background technique [0002] The assembly line scheduling of mechanical parts processing belongs to the assembly line scheduling. It is a typical production scheduling problem that is widely studied and applied. At the same time, it has many variables and is a complex combinatorial optimization problem that is strongly NP-hard. Reasonable scheduling is the core content of production management. With the increasingly intensified market competition and the diversification and individualization of customer needs, the production of enterprises is gradually developing in the direction of "multiple varieties, small batches, fast delivery, and less inventory". Scheduling is even more impor...

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Problems solved by technology

However, this algorithm can only be used for continuous space search, and cannot be directly applied to discrete combinatorial optimization problems.

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