Change of machine layout is often required for small quantity and diversified orders in the apparel manufacturing industry. The purpose of this paper is to use a hierarchical order‐based genetic algorithm to quickly identify an optimal layout that effectively shortens the distance among cutting pieces, thereby reducing production costs.
The chromosomes of the hierarchical order‐based genetic algorithm consist of the control genes and the modular genes to acquire the parametric genes, a precedence matrix and a from‐to matrix to calculate the distance among cutting pieces.
The paper used a men's shirt manufacturing as an example for testing the results of a U‐shaped single‐row machine layout to quickly determine an optimal layout and improve effectiveness by approximately 21.4 percent.
The manufacturing order is known. The machine layout is in a linear single‐row flow path. The machine layout of the sewing department is independently planned.
The advantage of the hierarchical order‐based genetic algorithm proposed is that it is able to make random and global searches to determine the optimal solution for multiple sites simultaneously and also to increase algorithm efficiency and shorten the distance among cutting pieces effectively according to manufacturing order and limited conditions.
