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Scheduling method based on multi-strategy water wave optimization algorithm

A technology for optimizing algorithms and scheduling methods, applied in computing, computing models, manufacturing computing systems, etc., can solve problems such as algorithms and optimizers that are difficult to show optimal performance, and achieve the effect of a simple framework

Pending Publication Date: 2022-02-18
LANZHOU UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

However, according to the no free lunch theorem, many algorithms and optimizers are difficult to show optimal performance on specific optimization problems in a certain field

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  • Scheduling method based on multi-strategy water wave optimization algorithm
  • Scheduling method based on multi-strategy water wave optimization algorithm
  • Scheduling method based on multi-strategy water wave optimization algorithm

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Embodiment Construction

[0026] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific examples described here are only used to explain the present invention, not to limit the present invention.

[0027] Such as figure 1 As shown, a scheduling method based on the multi-strategy water wave optimization algorithm, the scheduling method includes a continuous function optimization problem solving module, a zero-idle flow shop scheduling solution module, and a distributed zero-idle flow shop scheduling solution module with an assembly process.

[0028] In the example of the present invention, firstly, corresponding modules are called to optimize and solve the continuous function optimization problem. A scheduling method based on a multi-strategy water wave optimization algorithm, comprising the following steps:

[0029] Step 1: Generate the initial population NP through the reverse learning s...

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Abstract

The invention discloses a scheduling method based on a multi-strategy water wave optimization algorithm. According to an operation mechanism of a water wave optimization algorithm and problem characteristics of three operations in the algorithm, the method mainly comprises the steps that for a continuous optimization problem, the water wave algorithm based on reverse learning and a covariance matrix adaptive evolution method is proposed, and refraction operation of the original water wave algorithm is replaced by updating a population with a covariance matrix to improve population diversity. In the zero idle flow shop scheduling problem, a skewness and variable coefficient combined method is provided for an initialized population to generate an initial sequence population to improve population stability, and a neighborhood search method based on different three operation operation attributes is provided. According to a distributed zero-idle flow shop scheduling problem with an assembly process, machine learning and variable neighborhood search are introduced, so that a proposed algorithm obtains a high-quality solution within limited time through training and reward in an iterative updating process. The method has the advantages of being simple in frame, easy to implement and clear in logic.

Description

technical field [0001] The invention belongs to the field of manufacturing production scheduling, and in particular relates to a scheduling method based on a multi-strategy water wave optimization algorithm. Background technique [0002] The production scheduling problem is a process that requires reasonable use and arrangement of existing resources within a limited time in order to maximize the production benefits of the enterprise. Usually, the classic flow shop scheduling problem regards the equipment capacity as infinite. However, in real life, it is necessary to arrange the production reasonably within the limited time of the equipment so that the workpiece is constrained by the equipment capacity during scheduling. Therefore, the equipment capacity constraint The job shop scheduling problem is more complex than the classic flow shop scheduling problem. At present, the core of solving the problem of improving resource utilization and production efficiency is to constru...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/04G06N3/00
CPCG06Q10/0631G06Q50/04G06N3/006Y02P90/30
Inventor 赵付青张丽欣曹洁陈作汉张建林唐建新
Owner LANZHOU UNIVERSITY OF TECHNOLOGY
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