In this study, a new multiobjective JRD model with stochastic demand is proposed which takes into account the service level while making the replenishment and delivery decisions.
To our best knowledge, this is the first time to propose a practical multiobjective stochastic JRD model.
(2) The MOEA is adopted to solve the proposed multiobjective JRD model.
The future research on the multiobjective JRD problem should consider more realistic assumptions such as uncertain costs, freight consolidation, and budget constraint.
In order to discuss the JRD problem, the following notations are defined:
Proposed Fuzzy Multiobjective JRD (M-JRD) Model and Analysis
The signed distance method is simple and easy to handle, and this is why the extension principle and centroid method are not applied to this fuzzy JRD model.
In practice, the goal of JRD policy cannot be confirmed exactly due to inevitable uncertainty.
But, the effectiveness of DEs for the fuzzy JRD should be studied further because of the difficult mathematical properties.
We consider that RAND algorithm mentioned in Section 3.4 can obtain the optimum solution for the crisp JRD model.
(3) RAND_JRD: A Modified Algorithm for the Defuzzified JRD. Cha et al.
We developed a practical JRD model under uncertainty and provided an effective algorithm for this model.