Search results

This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

In view of the difficulty in determining the key parameters d in the Corten-Dolan model, based on the introduction of small loads, damage degrees and stress states to the Corten-Dolan model and the existing improved model, the sequential effects of the adjacent two-stage load were further considered.

Two improved Corten-Dolan models were established on the basis of modifying the parameter d by two different methods, namely, increasing stress ratio coefficient as well as considering the effects of loading sequence and damage degree as independent influencing factors respectively. According to the test data of the welded joints of common materials (standard 45 steel), alloy materials (standard 16Mn steel) and Q235B steel, the validity and feasibility of the above two improved models for fatigue life prediction were verified.

Results show that, compared with the traditional Miner model and the existing Corten-Dolan improved model, the two improved models have higher prediction accuracy in the fatigue life prediction of welding materials whether under two-stage load or multi-stage load.

Because the mathematical expressions of the models are relatively simple and need no multi-layer iterative calculation, it is convenient to predict the fatigue life of welded structure in practical engineering.

The major marine functional zoning plan (MMFZP) and marine functional zoning (MFZ) are two important kinds of marine spatial planning (MSP) in China. Their developing and implementation are integral to rational marine utilization and sustainable marine development. The purpose of this research is to study how these two kinds of MSP work in coordination in China.

This paper reviewed the present status of MSP research in China and abroad and presented a comparative study of the MMFZP and MFZ from different aspects, analyzing the relationship between the two.

The study found obvious differences between the MMFZP and MFZ, with respect to their concept and connotation, purpose and goal, as well as zoning methods and zoning functions. MFZ provides reference with respect to data, zoning methods and partial zoning results for the MMFZP, which in turn takes measures for addressing issues faced by MFZ and promotes the national MSP work.

In the process of developing and implementing the two zoning plans, this paper emphasizes the necessity to strengthen data sharing, reference of zoning techniques and coordination in zoning work, which will help to improve China's marine spatial management.