An Improvement of Silver's Algorithm for the Joint Replenishment Problem

A sensitivity analysis of solving joint replenishment problems using the RAND method under inaccurate holding cost estimates and demand forecasts

“…Kaspi and Rosenblatt reviewed and compared six approaches proposed for solving the JRP. They recommended adopting their heuristic in 1983 (Kaspi & Rosenblatt, 1983) if no iterative procedure is desired. They also proposed the heuristic they found was most suitable when iterations were allowed.…”

Solving the multi-buyer joint replenishment problem with the RAND method

“…Then, we can get the flow chart as follows: (Fig. 1) Note that Silver's modified heuristic (Kasp & Rosenblatt, 1983) is applied in an iterative way until the values of k i converge. In conducting their simulation experiments, Kasp and Rosenblatt (1983) found that the major improvement of the algorithm occur in the first iteration.…”

“…1) Note that Silver's modified heuristic (Kasp & Rosenblatt, 1983) is applied in an iterative way until the values of k i converge. In conducting their simulation experiments, Kasp and Rosenblatt (1983) found that the major improvement of the algorithm occur in the first iteration. In the current study, we employ the better estimate for T min given by Goyal and Deshmukh (1993).…”

A class of random algorithms for inventory cycle offsetting

“…In joint replenishment policy, usually a base cycle is determined, and the cycle of any item is an integer multiple of the base cycle. So this approach is also called the base cycle approach (c.f., Goyal (1973), Silver (1976), Goyal and Belton (1979), Kapsi and Rosenblatt (1983)). It can be shown when the base cycle length is given, the problem of determining the integer multiples can be regarded as a partitioning problem and solved efficiently in most practical cases (c.f., Chakravarty et al (1982), Chakravarty et al (1985)).…”