Date of Award


Degree Type


Degree Name

Master of Science in Industrial Engineering (MSIE)


Industrial Engineering

First Advisor

Shimon Y. Nof

Second Advisor

Vaneet Aggarwal

Committee Chair

Shimon Y. Nof

Committee Co-Chair

Vaneet Aggarwal

Committee Member 1

Andrew Liu


Along with tremendous growth of online sales in this Internet era, unprecedented intensive competition in shortening the delivery time of orders has been occurring among several major online retailers. On the other hand, the idea of customer-oriented service creates a trend of diversified pricing strategy. Different price options are offered to cater to diversified needs of customers. It has become an urgent need for online sales industries to provide the differentiated service levels for different classes of customers with different priorities based on the charging prices and resource constraints of the supply network.

In response to the challenges mentioned above, this thesis focuses on providing differentiated service levels to different customers within the warehouse automation system, which is the key point of the supply network. To concentrate on the research topic, the process of a user’s order in warehouse automation system is broken down into the waiting process and retrieving process, which is related to order processing policy and storage assignment method respectively.

Priority Based Turn-over Rate (PBTR) storage assignment method, Priority Based Weighted Queuing (PBWQ) policy and joint optimization of storage assignment and PBWQ policy are proposed, developed, explored and validated in this thesis.

Utility function of charging price and order processing time is developed to measure the performances of the proposed methods. Compared with the classical turn over rate assignment method, PBTR has 23.21% of improvement under the measurement of utility function, when different classes of customers have different needs for products. PBWQ improves the system performance by 18.15% compared with First-Come-First-Serve (FCFS) policy under baseline setting of experiments. Joint optimization of storage assignment and PBWQ policy has the improvement of 19.64% in system performance compared with the baseline system which applies both classical storage assignment method and FCFS order processing policy.