Double-resource die job shop scheduling optimization method based on AMAS-GA nested algorithm

Abstract

The invention discloses a double-resource die job shop scheduling optimization method based on an AMAS-GA nested algorithm. On the basis of comprehensively analyzing energy consumption, completion time and equipment and personnel load conditions of a workshop, a double-resource job shop multi-target scheduling problem model is established, wherein the load balance condition of equipment and personnel is measured by calculating the standard deviation of the accumulated load of the equipment and personnel, and the energy consumption of the shop considers the energy consumption of the equipment in standby and processing states; secondly, an AMMS-GA nested algorithm is designed to carry out scheduling model optimization solution, and procedure sorting is carried out by adopting a genetic algorithm by an inner layer according to a resource selection result as a constraint; and finally, a scheduling scheme result is fed back to an outer layer algorithm to influence selection of ants on resources. The method can be used for workshop scheduling and production scheduling, the workshop production efficiency is improved, energy consumption is reduced, green and energy-saving production is promoted, and meanwhile equipment and personnel load balance in production can be met.

Description

technical field [0001] The invention relates to job shop scheduling technology, in particular to a dual-resource job shop scheduling modeling and optimization method, especially for digital job shops for mold production using high-end numerical control processing equipment, and belongs to the technical field of intelligent manufacturing and scheduling. Background technique [0002] The job shop scheduling problem is a kind of resource allocation problem that satisfies the task configuration and sequence constraints, and is a typical NP problem. Among them, the scheduling problem when only machine tool resources are constrained is called the single resource scheduling problem; but in actual production, the operator of the equipment is often a very common constrained resource, and the types of equipment that can be operated by different operators and The numbers are generally different; therefore, the scheduling problem in which the two resources of processing equipment and op...

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Problems solved by technology

Ant colony algorithm has the following advantages: positive feedback, strong robustness, distributed computing, easy to combine with other algorithms, etc.; at the same time, it also has its own shortcomings: it requires a long calculation time, and it is easy to fall into local optimum and stagnate.

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