| Abstrakt: |
Efficient inventory management is crucial for businesses handling deteriorating products due to the increased risk of obsolescence and loss of value over time. This research delves into the production life-cycle stages specifically designed for deteriorating products and introduces a categorization into the following stages: initial, growing, maturity, declining, and shortage. Each stage is defined and analyzed mathematically, accompanied by strategies for effective inventory management. Through this framework, manufacturers can streamline their inventory processes, reduce costs, minimize waste, and maximize profitability. Additionally, this study incorporates the rework process into the inventory management framework, addressing the complexities of dealing with imperfect and deteriorating items. By integrating rework, businesses can further optimize their inventory levels and enhance product quality, leading to improved overall efficiency. To optimize the complex profit function associated with deteriorating products, the study employs the Grey Wolf Optimizer and Ant Colony Optimizer algorithms. These meta-heuristic optimization techniques provide robust solutions to intricate inventory management challenges, enabling businesses to adapt dynamically to fluctuating market conditions and changing demand patterns. A key result of this study is that the hybrid approach of combining GWO and ACO significantly reduces total costs, including production, rework, holding, and shortage costs, thereby improving profitability and resource efficiency. The managerial implications include offering decision-makers actionable insights on resource allocation across different stages of the production life-cycle. Furthermore, this research highlights the importance of proactive planning and strategic decision-making in mitigating risks associated with deteriorating products. Ultimately, this approach enhances competitiveness and long-term sustainability in the marketplace. [ABSTRACT FROM AUTHOR] |
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