class-based storage

In the global supply chain, warehouses play a significant role, yet the construction land for warehouse areas is decreasing. This issue requires the company to discover a method of optimizing the available warehouse area under various policies. This article contains a systematic review of class-based storage articles that becomes essential due to the absence of the latest and comprehensive similar literature. This study aims to analyze various policies for optimizing warehouse functions and provide direction for opportunities for future research in sustainable topics. A systematic review is employed in this study to search for articles from 2004-2023 originating from four journal databases, which are ScienceDirect, Emerald, tnfonline, and Researchgate; to be later organized based on the procedures of systematic literature review (SLR). The research results show various aspects, such as the purpose of conducting the research, the findings in the article, the impact of the results influencing the optimization of warehouse functions, and the gaps in previous studies, which are opportunities for future research to create more complex and comprehensive research results on similar research topics. It is expected that this study could contribute to filling in the theoretical gap by completing the existing literature. Therefore, scientific value can be added by presenting the newest comprehensive literature review.

An integrated optimization framework, including location assignment under grouping class-based storage policy and schedule of dual shuttle cranes, is offered by presenting a new optimization programming model. The objective functions, which are considered at this level, are the minimization of total costs and energy consumption. Scheduling of dual shuttle cranes among specified locations, which were determined in the upper-level, is conducted in the lower-level by considering time windows and balance constraints under multi-period planning conditions. A modified nested differential evolution-based algorithm is introduced to solve the proposed model because it is an Np-hard bi-level bi-objective optimization model. Eventually, with the intention of illustrating the validation of the presented optimization model and solution methodology, various numerical experiments are tailored, and different comparative numerical examples are provided based on two current algorithms in the literature. Sensitivity analyses illustrate that grouping class-based storage policy could be rendered superior planning of operations in both levels of the investigated problem.