Project Details
Projekt
Strategies and quantitative approaches for workload balancing in stochastic order fulfilment systems
Applicant
Dr.-Ing. Uta Mohring
Subject Area
Production Systems, Operations Management, Quality Management and Factory Planning
Operations Management and Computer Science for Business Administration
Operations Management and Computer Science for Business Administration
Term
since 2023
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 522967295
On-time fulfilment of customer-specific orders is omnipresent in supply chain management. Order fulfilment systems, e.g. warehouses, logistics service providers, online retailers, are recently confronted with multiple challenges: (1) They face a time-dependent, uncertain, and highly volatile customer demand volume and several system-inherent uncertainties; (2) Customers expect them to provide flexible and reliable customer-oriented service and short delivery times; (3) They operate against fixed deadlines as the completed orders are consolidated to large transportation batches for delivery and there is a daily delivery schedule with predefined vehicle departure times. Workload balancing provides a promising approach to manage the conflict between high customer satisfaction and operations efficiency in this challenging environment. It aims at balancing volatile system workload over a given time horizon. There is a plethora of balancing approaches in order fulfilment. However, they have been barely studied in the literature so far. My overall research goals are developing and analysing sophisticated strategies and quantitative models for workload balancing that enable efficient operations management of order fulfilment. My PhD thesis represents the initial step towards these goals. By introducing and investigating the Strategy of Levelled Order Release (LOR), it contributes to research on “Balancing system workload over time”. The proposed research project makes a significant further contribution to achieving my overall research goals. Its contribution is two-fold: (1) It continues and enhances research on “Balancing system workload over time” by exploiting and combining the potentials of the variability buffers time, capacity and inventory in order fulfilment. I will introduce and investigate strategies for workload balancing over time that extend LOR by approaches of capacity flexibility. (2) The proposed research project opens up a new balancing approach: “Balancing customer demand volume over time”. I will introduce and investigate strategies for demand management that dynamically adapt the service options offered to the customers and their prices such that the resulting customer demand volume fits as well as possible to the given capacity. For both balancing approaches, I will define and formalise several balancing strategies. These strategies are then investigated and configured using Markov chain models, sample-path analysis and derivative-free optimisation algorithms. Finally, an extensive numerical study, comprising multiple performance indicators and different types of order fulfilment systems, will enable a comprehensive analysis of the balancing strategies. It allows quantifying the general benefit of workload balancing in order fulfilment and generates insights on effective workload balancing, e.g. when to prefer working time accounts over temporary workers or when and how to adapt the offered service options and their prices.
DFG Programme
WBP Fellowship
International Connection
Netherlands
