An explicitly dynamic competitive facilities location model

• Main Author: Gobaco, Bryan O.
• Format: text
• Language: English
• Published: Animo Repository 2002
• Subjects: Mathematical models; Plant engineering; Facility management; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/2939
• Institution: De La Salle University

Previous studies in competitive facilities location have almost always considered a single period problem with static treatment of market conditions. Location problems are strategic in nature. Location decisions are always made for the long term and any decisions in a period will affect decisions that will be made in subsequent ones. This study deals with a multiple period competitive facilities location problem. A multiple period consideration allows for incorporation of shifts and changes in market conditions when making location decisions. Thus, the long term strategic characteristic of location problems can be more appropriately captured. Facilities are treated to be explicitly dynamic while customers patronize the facility that will provide them the highest amount of satisfaction. The satisfaction that can be derived by a customer from a facility is measured by a deterministic utility attraction function. Capacity restriction of facilities, which often is neglected in previous researches, is considered fully in this paper as capacity of opened facilities is to be determined along with its quality. The competitive location problem dealt with in this paper is therefore concerned with finding the location and design (quality and capacity) strategy that will maximize the expected discounted profit that could be earned over a chosen planning horizon. A mixed integer nonlinear programming (MINLP) model was formulated for the competitive location problem described. Convexity analysis guaranteed that an optimal solution exists. However, it might be computationally burdensome to arrive at this solution as indicated by the model's derived complexity function.Through validation and sensitivity analysis, it was seen that multi-period competitive location models could make better facility siting and design decisions compared to models limited to a single period. The optimal location and design strategy yielded by the model was also shown to be robust up to certain extent of violation in the novelty orientation assumption and variation in customer demand. It was also ascertained that capital expenditures allotted for investments in establishing and designing facilities could affect long run profitability performance of a company.