Omni-channel order fulfilment and cross-channel integration : solving a real-size problem

Abstract

Due to constant disruptions in the supply chains and increasing customer demands, businesses are more complex than ever before. An omni-channel business is a customer-centric approach in which all shopping and delivery operations are seamlessly integrated, so the customer has a unified and consistent experience whether they are in store or shopping online. A well-integrated omnichannel business can reap the benefits of creating synergy between channels and reducing operational costs. However, running an omni-channel business introduces new planning challenges such as synchronising the order fulfilment process between channels and optimising customer delivery costs. Academic research in omni-channel is still in its infancy, especially with mathematical modelling efforts being very limited but picking up on quantitative analyses and decision-making research in recent times. Order fulfilment and customer delivery are among the least investigated topics in the omni-channel literature. This research thus seeks to contribute to filling the gap in the omni-channel literature. With this in mind, mathematical modelling of order fulfilment can help omni-channel practitioners profitably serve their customers while offering them the comfort of home delivery or pick up at a chosen location. A common modelling challenge in this context is that solving the delivery model with respect to the whole network adds to the complexity of modelling efforts due to the additional variables and constraints such as inventory at each location, distances, transport rates, etc. Most attempts in the literature have focused on small-scale problems with a limited number of variables rather than real-size problems based on industry-scale scenarios. Motivated by the existing literature gaps in omni-channel research and real-life business challenges, the Smart Omni-Channel Fulfilment (SOChaF) model is developed in this thesis. The SOChaF model aims to minimise the total cost while fully meeting customers’ demand for flexible shopping and delivery. This research contributes to the omni-channel research with a new model for cost-optimised order fulfilment and in an omni-channel retailer, via employing an enhanced Genetic Algorithm. This is powered by an efficient data processing approach by pairing the solution algorithm with an SQL database for data aggregation and processing in database engine layer instead of application layer. The software application to run the enhanced Genetic Algorithm has been developed as part of this thesis. The practical relevance of the SOChaF model to omni-channel practitioners is shown by its use in solving real-size problems (i.e. with the total number of products and locations in a national omni-channel retailer in Australia) that require optimising the cost of order fulfilment in a very short span of time. The proposed model optimises the total cost through cross-channel integration when allocating the orders to different facilities throughout Australia.

Date of Award	2023
Original language	English