An Evaluation of the Solution Algorithms for the Joint Replenishment Problem
The Joint Replenishment Problem (JRP) determines lot sizes and schedules replenishment times for products so as to minimize the total costs per unit time. In literature, many solution approaches have been proposed to solve the JRP. In this study, we address our efforts to critically evaluate the search algorithms for the JRP. To do so, we first review the of the JRP, investigate the questionable issues in those algorithms, and scrutinize the reason why they are not able to efficiently solve the optimal solution. Also, we employ an example to verify our critical evaluation to show the questionable issues. To compare the computational performance, we test these search algorithms by random experiments. Based on our experimental results, we conclude that Yao and Lee's(2001) algorithm out-performs van Eijs'(1993) algorithm, Viswanathan's (1996) heuristic and Wildeman et al.'s(1997) Lipschitz-based algorithm.
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