Product change scheme design method based on multi-objective particle swarm optimization

Abstract

The invention discloses a product change scheme design method based on multi-objective particle swarm optimization. The method comprises the following steps: establishing a complex product multi-network model with introduced service performance for any given to-be-changed product; through decoupling the influence of the strong association node on the service performance in change effect propagation, generating a multi-target solution model containing three evaluation indexes of the service performance influence degree, the change cost and the change time; adopting an integer type multi-target particle swarm optimization algorithm for solving the multi-target model, and obtaining a group of optimal change schemes; and finally, solving an optimal change scheme meeting the user requirements by using a fuzzy decision-making method. According to the method, the operability of the obtained change scheme is higher, the obtained change scheme can cover the key nodes on the multiple propagation paths at the same time, and the actual design requirement is better met. By setting proper constraint conditions, the feasibility of changing the scheme can be ensured to the greatest extent.

Description

technical field [0001] The invention belongs to the field of product design, and in particular relates to a method for designing a product change plan based on multi-objective particle swarm optimization. Background technique [0002] Design change is an inevitable link in the product development process, and an unreasonable design change plan will not only increase the cost of product development, but also significantly affect the service performance of the product. In actual production, affected by subjective and objective reasons such as iterative product upgrades, supply chain breaks and blockages, and revisions of laws and regulations, it is often necessary to redesign or select product parts. More importantly, changes to one critical part propagate and affect other related parts in the product. For complex product design (CPD) problems with a large number of parts and close connections, if the product design change process is not effectively analyzed and controlled, t...

AI Technical Summary

Problems solved by technology

After determining the optimal change propagation path, existing modeling methods consider that all affected nodes in the path need to be changed

However, in reality, it is often difficult or even impossible to change some parts

If such parts happen to be included in the selected optimal path, the path cannot be implemented or the implementation cost is unacceptable

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