Performance Analysis and Optimization in Stochastic Service and Manufacturing Systems with Customer Choices

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Uncertainties exist when purchasing a product or service and the perceived quality from a customer's perspective impacts both the provider and receiver of the goods and services. The aim of my research is two-fold: (1) to find cost effective ways to reduce congestion of customer service systems with limited service capacity via stochastic modeling and analysis; and (2) to design the optimal preventive maintenance schedule and warranty policy to improve the reliability of the system or product subject to random failures. The first aim will be achieved by first, continuing research on joint decision of pricing and capacity for service firms in a competitive environment and second, by finding the optimal resource allocation in a stochastic service system within two different service facilities to minimize the overall operating and customer waiting cost. The second aim will be achieved by analyzing the cost behaviour of a free-repair warranty policy combined with a preventive maintenance schedule and optimizing a warranty policy for the product sold. Compared with classical queuing models, the proposed research is innovative in its use of new queuing models addressing the congestion issues for multi-channel service systems with customer choice and for more general multi-server service systems with differentiated server groups (called group-server queues). The proposed research is highly relevant to the challenges faced by governments at the Provincial and Federal level such as the provincially run healthcare systems, Canada-US border crossing systems, and Canadian airports' security checkpoints. For example, research findings can support the work of agencies such as Canada Border Services Agency in managing border operations effectively, balancing security and public safety needs with efficient travel and trade. Work on competition and coordination of public and private service systems is highly relevant to Canada's healthcare system. While politicians in Canada continue to debate the viability of a two-tier public and private healthcare system (as they already exists in Australia and the UK), no quantitative congestion analysis for evaluating such a system exists. Outputs from my research will make a significant contribution to the ability of governments to design sustainable, shorter or no waiting for services within an affordable healthcare system. In addition, the results of group server queue model can be used to design energy-efficient large data centers in Canada (e.g., Toronto Data Centre). The proposed work on reliability improvement for consumer products will help Canadian manufacturers (e.g., Bombardier) to improve the product reliability in a highly competitive global market.