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Job shop scheduling method based on discrete invasive weed algorithm

A technology for job workshops and scheduling methods, applied in computing, computing models, instruments, etc., can solve problems such as unstable operation results, long computing time, and poor accuracy, and achieve the effect of enhancing local search capabilities and deep search capabilities

Inactive Publication Date: 2019-11-15
LANZHOU UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

The algorithm is proposed to solve the shortcomings of the current algorithm, such as unstable operation results, long calculation time, poor precision, and no theoretical guidance for convergence.

Method used

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  • Job shop scheduling method based on discrete invasive weed algorithm
  • Job shop scheduling method based on discrete invasive weed algorithm
  • Job shop scheduling method based on discrete invasive weed algorithm

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Embodiment Construction

[0036] The application of the job shop scheduling method based on the discrete invasive weed algorithm:

[0037] There are M machines in the job shop scheduling problem, expressed as [1,2,..k,m,...,M], m and k are each a machine in the scheduling problem, and m≠k. Each machine can only process one process, and the process on each machine is different; the completion time of different workpieces on different machines is independent of each other, and it is guaranteed that all machines will not fail.

[0038] There are N workpieces to be processed in the job shop scheduling problem, expressed as: [1,2,..i,n,…,N], i and n are each a job in the scheduling problem, and n≠i. Each job can be processed in a different sequence, with independent completion times.

[0039] Suppose the completion time of job n on machine m is C n,m ;The processing time of workpiece n on machine m is l n,m ; When the goal of job shop scheduling is to minimize the maximum completion time, the objective f...

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Abstract

The invention discloses a scheduling method based on a discrete invasive weed algorithm, and the algorithm comprises the steps: giving an initial solution of a random number to all weeds, and carryingout the coding and decoding of an initial random sequence in a mode of procedure coding; in each iteration process, enabling each weed to calculate the number of seeds to be generated by the weed; inthe spatial diffusion operation of the algorithm, enabling the seeds to generate a standard deviation value for controlling the diffusion distance according to the fitness value of the parent plant,and enabling the seeds to be randomly diffused around the parent in a normal distribution mode according to the standard deviation value; carrying out local optimization on newly generated seeds, using a VNS thought to change a sequence of a workpiece, and improving the local search capability of the algorithm; and when the total number of the weeds reaches a set maximum value, removing poorer individuals by an algorithm, and only retaining the maximum number of the weeds. The invention provides a scheduling method based on an advanced novel evolutionary algorithm, and the scheduling method can more intelligently solve the job shop scheduling problem in the manufacturing industry.

Description

technical field [0001] The invention relates to the field of production line scheduling in the manufacturing industry, in particular to a method for optimizing the job shop scheduling problem in the production scheduling environment. Background technique [0002] Job Shop Scheduling Problem (JSP) is a very important problem in manufacturing production scheduling. At the same time, the field of application of the job shop scheduling problem is also very wide. In addition to the production scheduling of the manufacturing industry, it also involves practical issues such as aircraft carrier scheduling, airport aircraft scheduling, port wharf cargo ship scheduling, and automobile processing assembly line scheduling. Therefore, it is very important to study the workshop scheduling, and the traditional mathematical method has been unable to meet the needs of production scheduling. At present, most scholars use approximate algorithms to solve such problems, and a large branch of th...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06N3/00
CPCG06Q10/06312G06N3/006
Inventor 赵付青逯浩唐建新张建林
Owner LANZHOU UNIVERSITY OF TECHNOLOGY
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