Batching and stock layout iterative optimization method based on blanking utilization rate prediction

Abstract

The invention discloses a batching and stock layout iterative optimization method based on blanking utilization rate prediction, and the method comprises the following steps: order batching: carryingout the order batching optimization according to an order agglomeration hierarchical clustering algorithm meeting delivery date deviation and production constraints, and obtaining a plurality of feasible batching schemes; feature extraction and dimension reduction: taking the plates of the same material in each batch in each batch scheme as a minimum prediction sample; inputting the prediction model to obtain a prediction result; inputting all minimum prediction samples in each batch scheme into the blanking utilization rate prediction model to predict a layout result, and calculating layout prediction results of all materials in all batches in the batch scheme; calculating and evaluating a layout prediction result; calling a layout optimization algorithm for calculation; judging and outputting a result. The invention aims to provide the batching and stock layout iterative optimization method based on blanking utilization rate prediction, the utilization rate of raw materials can be greatly improved, the cost of the raw materials can be reduced, and the calculation time can be greatly shortened.

Description

technical field [0001] The invention relates to the field of plate typesetting optimization, in particular to an iterative optimization method for batching and layout based on the prediction of blanking utilization rate. Background technique [0002] Panel furniture is a mainstream furniture with personalized design, beautiful and fashionable, efficient space utilization, stable quality and affordable price. It has the characteristics of customization, environmental protection and practicality. Panel furniture refers to furniture made of wood-based panels such as plywood, particle board, MDF, and gentry board as component substrates, and assembled with connectors. Its composition has the structural characteristics of "standardized components + hardware interfaces". Compared with solid wood furniture, it has many advantages such as customizable appearance design, various product styles, not easy to deform materials, simple disassembly and installation, convenient transportati...

AI Technical Summary

Problems solved by technology

[0004] The order batching process is a combinatorial optimization problem. Orders are combined according to actual production constraints and delivery dates. If all possible permutations and combinations are combined, it may be feasible for a small number of order combinations, but for relatively large orders , the types of grouping schemes generated by exhaustive enumeration will be very large

The layout optimization problem is an NP-hard problem, the search and solution space of the layout problem is huge, and the calculation takes a long time

If the order is batched in the conventional way, and the optimization algorithm for plate layout is called directly, the layout result, that is, the utilization rate, once it is unsatisfactory, the next iteration (replacing the batching scheme) will be performed. This iterative method will not be able to ensure the solution process. The convergence speed and the quality of the solution will eventually lead to the entire solution process becoming very long

In order to adapt to small-batch, multi-variety, and large-scale orders for kneading single production, and to avoid problems such as low blanking rate of some plates, long calculation time, low production efficiency and unsatisfactory delivery due to the above method, a method based on The historical data-driven blanking utilization forecasting model realizes the iterative optimization of order batching and layout by quickly screening the batching scheme through the forecasting model

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