A developed mobile application for optimum facility location using center of gravity approach

• Main Authors: Gutierrez, Ma. Teodora E., Naval, Japeth Q., Paulite, Elyza May S., Morco, Roselia C., Acerado, Risty M., Mutuc, Jose Edgar S.
• Format: text
• Published: Animo Repository 2018
• Subjects: Center of mass; Mobile computing; Mobile apps; Mobile geographic information systems; Artificial intelligence; Industrial Engineering; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2561
• Institution: De La Salle University

This research is about the development, testing and application of mobile app for optimum location spot of a single facility. The approach is to use Center of Gravity Method to locate the central locations of the facility. This equality would reflect balance and minimum time and cost. The main variables to be considered in the systems are customer's distance, customer's demands and transportation rates. In general, firms which apply technologies will perform significantly better than those that do not. This leads to the development of a mobile app to identify best location for a single facility which will serve several demand centers. After the development of a mobile app, this undergoes testing which includes verification whether the mobile app will provide the same result in theoretical computations. The study confirms that the mobile app is consistent with the theoretical computations for location planning. This mobile app becomes a decision support system suggesting that they can access this mobile app to improve the firm's performance on decision making. A faster and effective decision making since instead of manual computation which will take time, the computation will be in a few seconds plus you could visualize the geographic areas being investigated. Moreover, the mobile app is practical to implement because it is flexible and easy to use. The data needed is easy to gather. The mobile app can generate up to 100 iterations to ensure that global maxima is obtained. © 2018 IEEE.