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Fuzzy multiple objective production and inventory planning in canned seafood factory |
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| รหัสดีโอไอ | |
| Title | Fuzzy multiple objective production and inventory planning in canned seafood factory |
| Creator | Natthakrij Nipanutiyan |
| Contributor | Pisal Yenradee, Advisor |
| Publisher | Thammasat University |
| Publication Year | 2568 |
| Keyword | Production planning, Inventory control, Fuzzy, Decision-making, Mixed integer linear programming (MILP) |
| Abstract | The seafood processing industry faces uncertainty in raw material prices and customer demand, which directly affects production planning, inventory control, profit, and environmental performance. This study develops a mixed-integer linear programming model integrated with fuzzy multiple-objective linear programming to support production and inventory control decisions in a seafood processing system. The model considers a monthly planning horizon and includes key decisions such as raw material purchasing, cold room inventory, production allocation, labor utilization, warehouse inventory, and the opening decision of an additional production plant. Uncertain demand and raw material price are represented using triangular fuzzy parameters based on historical data. A double weighted average approach is applied to evaluate the combined effect of demand and price uncertainty. The model has two main objectives: maximizing total profit and minimizing total CO₂ emissions from cold room storage, production processes, and warehouse operations. Experimental scenarios are designed to analyze the effects of different demand and price conditions on production planning decisions and system performance. The results show that raw material prices have a major influence on total profit, while demand uncertainty affects production allocation, inventory levels, and capacity utilization. The compromise analysis also shows that CO₂ emissions can be reduced with only a small reduction in profit. Overall, the proposed model provides a decision-support framework for balancing economic performance and environmental impact in seafood production planning under uncertainty. |
