Discrete Optimization by Neural Network Technique and Its Application to Ship Structural Design

Abstract

On account of the industrial standard or of the inherent characteristic of the design variable, most of practical design optimizations are considered as combinatorial optimization problems. Recently, Hopfield and et al. showed that some combinatorial optimization problems can be programmed and solved on artificial neural network system minimizing the quadratic energy function. In this study, an algorithmic procedure with neural networks for solving combinatorial optimization problems is proposed. The method attains good feasible solutions by systematically changing the Lagrange multipliers for the constraints in the problem. The proposed method can be applied to both linear and quadratic programming problems with discrete control variables. Numerical example for the optimum design of a frame structure is provided to illustrate the basic properties and applicability of the proposed method. The method is also applied to the optimum design of midship section in a general cargo ship.