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Spatial layout optimization method based on discrete and heuristic evolutionary algorithms

A layout optimization and evolutionary algorithm technology, applied in the field of space resource optimization layout, can solve the problem of slow convergence speed of intelligent optimization algorithm

Active Publication Date: 2017-11-07
HARBIN INST OF TECH AT WEIHAI
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Problems solved by technology

The intelligent optimization algorithm has a slow convergence speed, but it can theoretically obtain the optimal solution to the problem

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  • Spatial layout optimization method based on discrete and heuristic evolutionary algorithms
  • Spatial layout optimization method based on discrete and heuristic evolutionary algorithms
  • Spatial layout optimization method based on discrete and heuristic evolutionary algorithms

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Embodiment Construction

[0117] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0118] The present invention studies the position placement of ship intermediate products in a limited space during the shipbuilding process, which belongs to the two-dimensional plane space layout, and aims to obtain the layout result with high space utilization rate; firstly, define the concepts related to the space layout problem.

[0119] Definition 1 Site: refers to the space resources that can be used for processing and stacking, such as segmented storage yards, assembled processing platforms, etc. Based on the characteristics of the site, the following assumptions are made: ① The site is a two-dimensional rectangle; ② There is no unoccupiable area inside the site space, and it can be divided arbitrarily;

[0120] For a rectangular site with length L and width W, after the site is discretized with a grid of m×m size according to the actua...

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Abstract

The invention relates to the technical field of optimized space resource layout during ship construction, in particular to a spatial layout optimization method based on discrete and heuristic evolutionary algorithms, and aims to solve the problem that production efficiency is restrained due to the fact that space resources are limited in a ship construction process. On the basis of discretizing geometrical information of a two-dimensional space and irregular layout pieces, a mathematical model for the spatial layout optimization problem is established, a solving algorithm for the problem is designed by combining a heuristic moving strategy with a genetic evolutionary algorithm, quality of an initial solution is improved by adopting a non-out-of-range initial population generation strategy, unrestraint conversion of the problem is realized by introducing an overlapping out-of-range penalty factor, the algorithms are verified through a simulation experiment, and a result of the simulation experiment shows that the algorithms have advantages in rate of convergence and solving quality.

Description

Technical field: [0001] The invention relates to the technical field of space resource optimization layout methods in the shipbuilding process, in particular to a space layout optimization method based on discretization and heuristic evolution algorithms. Background technique: [0002] As a bottleneck resource restricting production efficiency under the current shipbuilding mode, space resources are widely concerned by shipbuilding enterprises because of their optimal utilization problems in all aspects of shipbuilding. Therefore, it is of great significance to study the solution to the problem of spatial layout for improving the production efficiency of enterprises. [0003] The spatial layout problem of shipbuilding is the same as the nesting problem, which is an optimization problem to seek the optimal layout of the plane. From the perspective of the shape of the layout parts, for rectangular parts with simple geometric features, it can be solved directly by mathematical...

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Application Information

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IPC IPC(8): G06F17/50G06N3/12
CPCG06N3/126G06F30/15G06F30/20G06F2111/04
Inventor 张永健杨舟
Owner HARBIN INST OF TECH AT WEIHAI
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