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

A technology for job workshops and optimization methods, applied in control/regulation systems, instruments, and comprehensive factory control, etc., can solve problems such as stagnation and long calculation time, and achieve the effects of reducing energy consumption and improving workshop production efficiency

Active Publication Date: 2020-11-20
BEIJING UNIV OF TECH
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Ant colony algorithm has the following advantages: positive feedback, strong robustness, distributed computing, easy to combine with other algorith...

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

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Embodiment 1

[0151] Taking a mold manufacturing company as the background, there are 12 mold processing equipment and 8 equipment operators in the workshop. There are 8 production tasks in a certain scheduling cycle. Each production task includes several processing procedures. Each processing procedure can be processed in at least one Candidate equipment resources are completed, and each equipment has at least one candidate operator. First, group equipment according to equipment function types, and determine the optional operators for each equipment group, as shown in Table 2; select the corresponding available equipment for each process according to the requirements of the process type and the equipment function model, and form the operator of each process The list of available equipment is shown in Table 3; the processing time of each process is shown in Table 4 (time unit: min). The power table of each equipment is shown in Table 5 (power unit: kW).

[0152] Table 2 List of optional op...

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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...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41865G05B19/41885
Inventor 初红艳李瑞刘志峰赵凯林黄凯峰
Owner BEIJING UNIV OF TECH
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