For cases with imbalanced capacity demands and supplies, this paper analyzes the impact of dynamics and uncertainty in capacity information, and studies the multi-period dynamic capacity matching problem faced by third-party shared manufacturing platforms. We aim to provide a reference method for platforms to optimize the multi-period matching strategies.
To alleviate the demand-supply imbalance and avoid capacity losses due to its non-storability, we consider that the platform not only matches the current-period capacity demand and supply but also conducts cross-period matching. We formulate this problem as a multi-period stochastic dynamic capacity matching model and propose a solution method by integrating the characteristics of the capacity matching problem with the value function approximation policy.
The results verify the effectiveness of the proposed capacity matching model and the dynamic approximation algorithm. They also show that matching demand in advance alleviates the imbalance between the demand and supply in a single period and optimizes the multi-period matching strategy.
Focusing on the scenario where demand information is submitted in advance, this paper innovatively studies how and when to match dynamic production capacity under uncertainty. This research extends the previous studies and provides implications for the operations management of third-party shared manufacturing platforms.
