Design of a decision making model for apparel plant location

Apparel manufacturers’ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. Some researchers have proposed systematic selection methods for plant location but the weaknesses of these approaches were that the measuring values must be exact and numerical. Moreover, manufacturers are facing with difficulties during the decision-making process due to vague and subjective measures, particularly for variables which cannot be represented in terms of objective value, such as country risk, community facilities, etc. The decision on plant location thus mostly relies on the subjective tuition and assessment of manufacturers. This paper explains the construction of a decision making model for apparel plant location using both the feedforward neural network with error back-propagation (EBP) learning algorithm and fuzzy analytical hierarchy process (AHP). Significant variables concerning the selection of apparel plant location will be identified and input into proposed decision-making model for processing.