“The more interrelated decisions you tackle together, the more you truly optimize your network.” The PhD research of Marlies de Keizer shows, based on a study of the European Floricultural sector, that network designs improve when network control decisions and perishability of products are simultaneously taken into account. “Advancements in technology and knowledge make that there is no bound on optimizing optimization.”
What is logistics network design and control?
“When your market is expanding, when your DCs loose efficiency, these are changes that require careful thinking about the design of your logistics network (i.e. setting the structure of the network at a strategic level). When your customers want to be delivered faster, order more frequently in smaller quantities, these are changes that require careful thinking about the control of your logistics network (i.e. managing logistics operations at a tactical and operational level). But what happens to your stocks when a DC is added? Or what happens to your network when raw material is to be stored instead of finished products? The two problems, network design and network control, are interrelated”. Based on a study of the European floricultural sector, Marlies de Keizer shows the interrelatedness of the problems in her PhD research “Logistics network design & control: managing quality in a blooming sector” (2015). This research was part of the DaVinc3i project, which was started by a consortium of industry professionals and academics in 2011 and partly financed by Dinalog.
Why the floricultural sector?
“Floriculture is inseparably linked to the Netherlands. The profound knowledge of the Dutch on how to breed and grow cut flowers and potted plants, the Dutch flower auctions being the largest in the world, the adequate infrastructure to facilitate transport and logistics; it has made the Dutch floricultural sector to what it is today: the trading hub for Europe.”
“The floricultural sector is in the transition from a supply driven to a demand driven network. As a result, market requirements are changing. Customers want to be delivered faster, more frequently and in smaller quantities, and they are demanding a higher, guaranteed quality of the products. First, this asks for a more responsive network, which together with increasing demand uncertainty and a differentiation in markets, asks for integration of network design and network control decisions (i.e. network configuration decisions). Second, due to perishability of the products, product quality decays with every logistics operation and this needs to be incorporated in network configuration decisions.”
How can integrated design & control support the floricultural sector?
To find optimal network configurations, consisting of hub locations and allocations of customer order decoupling points to these hubs, Marlies conducted a scenario analysis. “Scenarios were defined for different types of chains and different levels of product quality decay. For each scenario, the optimal configuration was determined using a hybrid optimization-simulation approach. The optimal network configurations were furthermore evaluated on performance indicators related to efficiency, responsiveness and product quality“.
Results showed that cost benefits of up to 28% can be reached with the design of a hub network. “It is important though that the configuration of the hub network is adapted to the type of supply chain.” Also, the optimal logistics network configuration for cut flower supply chains is especially driven by the trade-off between responsiveness and product quality. Incorporating product quality decay in logistics network configuration furthermore creates a more reliable and profitable network. “We need to take in account that different product quality factors need to be incorporated, like the level of product quality decay and variability in product quality, to guarantee adequate quality for the products delivered to customers”.
What does it mean for the tools and techniques that are used?
Integration of network design and network control problems increases dynamics in the network. This necessitates the use of a hybrid optimization and simulation approach to solve the integrated problem. “A hybrid optimization and simulation approach is needed to really capture product quality decay when designing and configuring a logistics network for perishable products. This approach should control the level of detail with which product quality is incorporated in the optimization model, as more detail increases run times significantly while it not necessarily contributes to finding the best logistics network configuration. We should keep in mind though that a hybrid optimization and simulation approach is even more subjected to the specific problem setting than the development of a pure optimization model”.
How to get the best of all worlds?
The floricultural sector is one example which shows the added value of integrating network design and control decisions and thereby incorporating perishability of products. Similar studies could benefit sectors like the food, chemical or energy industry. Also, the same dynamics as for perishability could be modelled for time related aspects, which could benefit sectors in which service time is key.
Although it benefits to tackle network design and network control problems in an integrated way, it is often tackled separately in practice. According to Marlies, one of the obstacles is the structure of companies. “Due to functional silos, design and control problems are often the responsibility of different people and departments. In collaboration with EyeOn, we aim to break these silos and constitute a modelling paradigm, called Advanced Inventory and Network Optimization (AINO), in which every aspect of logistics network configuration is taken into account. Wouldn’t it be great when all interrelated decisions can be tackled in one model and a truly optimal network configuration can be found? With the advancements in technology and knowledge, the sky is the limit. It is my personal aim to each time find the best combination of techniques and tools to optimize optimization.”
Marlies is Supply Chain Analyst at Argusi.org. After her studies on Econometrics and Operations Research at the University of Tilburg (cum laude), Marlies has worked as logistics consultant and as software developer. Deepening her practical knowledge, she has then conducted a PhD study at the University of Wageningen. Marlies de Keizer PhD thesis is published and can be read at http://edepot.wur.nl/362451.