Study On Banking Facility Location Problem And Optimization

Banking facilities outlets, as the infrastructure providing financial services to customers, the reasonableness of its location have a serious impact on the bank’s operational efficiency and competitiveness, and the same impact on the bank’s regional investment costs and service efficiency as well. Taking into account the financial facility outlets has its own characteristics and rules as the service sector; they usually provide their products to the customers face to face because of the simultaneity of Supplied with allocation in the transaction process. Customer satisfaction, service quality and efficiency should be their most important goals because their customers are multi-types and the demand is also diversified when their products in the transaction process. In this paper, considering the strategic decisions, the above factors are analyzed. Combining queuing theory and location theory, this paper studies Banking Facility Location Problems under different situations. Different mathematical optimization models are built on different application background, a variety of heuristic algorithms are proposed and random simulated examples are given.Firstly, this paper gives the background and significance of Banking Facility Location Problems. Considering the disadvantages of the current study, we present innovations of this paper. Then gives the main contents of such kind of facility location problems, and the current research status are reviewed.Secondly, multi-type facilities and multi-type customers in banking facility location problems are studied. The banking industry should location their facilities reasonably in the view of multi-level and multi-type facilities to satisfy diverse customer demands in a competitive market. Considering the characteristics of banking facility locations, we propose a multi-level location model in the respect of multi-type facilities, and the objective is the maximum of service efficiency. We also solve this model with Genetic Algorithms. Secondly with the combination of queuing theory and covering theory, we studied banking facility location of multiple types of customers. We establish an integer mathematical programming model which goal is the maximum of expected profit covered by the demand. Neighborhood search algorithm and genetic algorithm are proposed, the effectiveness of the algorithm are tested with a small-scale example.Thirdly, Covering Location Problems based on cooperation and competitions are studied. Most existing location models have a hypothesis of pure competitive market environment when considering competition locations and most covering location problems based competition with the Huff gravity model and spatial interaction model, making the market share of the division in the actual situation is not entirely applicable. Based on covering models, we studied set covering problem and maximum coverage problems of banking facility locations under the conditions of cooperation and competition. We discussed the bank’s decision-making results under the condition of pure competitive, part of co-competition and full cooperation respectively. Models are proposed and solved. We made a comparative analysis of the profits and costs of the enterprises under different circumstances.Fourthly, the self-service banking outlets facility location and design issues are proposed. Considering the diversification of consumer demand, there are many self-service facilities to increase the convenience in addition to sub-centers, branches, outlets and so on. We extend classical P-median problems by the structure of the efficiency of the service function. Considering banking facility location in a competitive environment, by the introduction of the impact the attractive utility function of network quality and spatial interaction model, we establish a new Banking Facility Location Problem about Flow Interception Model at the same time. We solve the model by greedy algorithm. Experimental results are compared with exact methods to verify the effectiveness of the algorithm.Finally, a comprehensive summary of the paper and future research are discussed.