Abstract

Military uniforms serve as an essential symbol for servicemen and an important image of national and military dignity. The current military uniform size system in Taiwan, which features various types of military uniforms based on the body sizes of servicemen, was formulated in 1986. This size classification system includes numerous groups and is too complex, leading to inventory overstock, increased inventory cost and warehouse staff workload, and a waste of national defense resources. This study used support vector clustering (SVC) with genetic algorithm (GA) models to improve the upper garment size system for uniforms. The SVC technique was employed to classify sizes, and the GA technique was used to determine optimal parameter values for the SVC model. This paper developed an upper garment size system that can increase the fit of uniforms to servicemen’s body sizes and reduce the number of size groups, thereby alleviating warehouse staff workload and inventory cost.

Highlights

  • Military uniforms serve as a crucial symbol to servicemen and an essential factor for setting the national image

  • We summarize as follows: support vectors (SVs) reside on the cluster circumference, bounded support vectors (BSVs) reside outside the boundaries, and all other points reside inside the boundaries

  • We collected anthropometric data required in making uniforms for male military personnel and cluster the data using support vector clustering (SVC) with the genetic algorithm (GA) to improve the current military uniform size system in Taiwan

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Summary

Introduction

Military uniforms serve as a crucial symbol to servicemen and an essential factor for setting the national image. Uniforms that do not fit servicemen are often supplied because of numerous and complex classifications of uniform size. This causes overstocking, increased stock cost, increased warehouse staff workload, and wasted defense resources. A size system of military uniforms should, be established to estimate purchase proportions for all sizes and reduce problems regarding the size and number of uniforms that do not fit. This should decrease inventory, stock cost, and financial overstock

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