The capacity of a firm to accomplish its goals is financially compromised by degeneration of goods. A suitable preservation strategy to reduce degradation is a vital part of the managerial decisions. This study employs preservation technologies under uncertain demand to frame a continuous review inventory model with full back-ordering and the influence of promotional efforts. Survey of existing research finds few models with synchronised optimization over this entire scenario with all factors.The best values of the preservation cost and the two fractions of the cycle period when inventory is kept against the backorder part are determined to lower the total average cost. A mathematical model is built to incorporate these elements and numerical scenarios are presented to compare three possible approaches. In both crisp and fuzzy contexts, the sensitivity of the solution and decision variables concerning various inventory characteristics is investigated. Backorder duration is inversely proportional to the presence of preservation. The coefficient of preservation has a tipping point below which accepting the impact of undamped deterioration becomes more cost-effective. The total cost at the optimal point is more elastic to a reduction in base deterioration rate and relatively inelastic to its increase. Finally, this study proves that the preservation strategy converges over deterioration for the crisp case rather than the fuzzy case. It is expected the fuzzy case can provide better results, however, the crisp case provides lower total cost than the fuzzy case though it is slightly less efficient in per unit cost.
|Number of pages||30|
|Journal||RAIRO - Operations Research|
|Publication status||Published - 2022 Nov 1|
Bibliographical noteFunding Information:
This work is supported by National Research Foundation of Korea (NRF) grant, funded by the Korea Government (MSIT) (NRF-2020R1F1A1064460).
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science Applications
- Management Science and Operations Research