Abstract
Collaborative operations planning is a key element of modern supply chains. We introduce the collaborative multi-level lot-sizing problem with cost synergies. This arises if producers can realise reductions of their costs by providing more than one product in a specific time horizon. Since producers are typically not willing to reveal critical information, we propose a decentralised mechanism, where producers do not have to reveal their individual items costs. Additionally, a Genetic Algorithms-based centralised approach is developed, which we use for benchmarking. Our study shows that this approach comes very close to the a central plan, while in the decentralised one no critical information has to be shared. We compare the results to a myopic upstream planning approach, and show that these results are almost 12% worse than the centralised ones. All solution approaches are assessed on available test instances for problems without cost synergies. For the biggest available instances, the proposed centralised mechanism improves the best known solutions on average by 10.8%. The proposed decentralised mechanism can be applied to other problem classes, where collaborative decision makers aim for good plans under incomplete information.
Highlights
Firms acting in competitive environments are forced to collaborate with other players within their supply chain networks in order to overcome inefficiencies and to stay in business
Our study shows that this approach comes very close to the a central plan, while in the decentralised one no critical information has to be shared
We show that the decentralised mechanism, no critical information is shared, comes very close to the centralised solutions
Summary
Firms acting in competitive environments are forced to collaborate with other players within their supply chain networks in order to overcome inefficiencies and to stay in business. Several decentralised collaboration mechanisms for distributed multi-level lot-sizing problems have been presented in the literature While cost synergies seem to be a natural and highly practical extension, they have not been considered in the literature on distributed multi-level lot-sizing problems so far. We propose a decentralised mechanism to tackle the problem, where agents do not have to share sensitive information. It includes a GA-based approach to produce production plans. This mechanism is benchmarked against centralised solutions generated by a fully informed decision maker. All solution approaches are assessed on available test instances for problems without cost synergies This emphasises the strength of the proposed decentralised mechanism.
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