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 EPQ Inventory Model with Backorders and Energy Implications
Tác giả hoặc Nhóm tác giả: Hong-Nguyen Nguyen*, Matthieu Godichaud, Lionel Amodeo
Nơi đăng: IFAC-PapersOnLine; Số: Volume 56, Issue 2;Từ->đến trang: 8598-8603;Năm: 2023
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
With the scarcity of energy supply in the world and especially in the European region, energy price is soaring rapidly. Therefore, finding solutions to save energy is a top priority for manufacturers. This study introduces an EPQ inventory model that takes into account the correlation between production processes and energy consumption, while also allowing for backorders. The energy consumption during both production and non-production periods of the machine is computed. The energy consumption in EPQ policies is contingent upon the production rate and the machine's states (off or standby) during non-production phases. Utilizing the proposed resolution algorithm, the model under examination seeks to minimize the average total system cost while considering the production rate, cycle time, the initial production time of the cycle, and the optimal machine state during non-production periods. To demonstrate the formulated model, a numerical analysis is conducted, with a particular focus on the impact of allowing backorders.
ABSTRACT
With the scarcity of energy supply in the world and especially in the European region, energy price is soaring rapidly. Therefore, finding solutions to save energy is a top priority for manufacturers. This study introduces an EPQ inventory model that takes into account the correlation between production processes and energy consumption, while also allowing for backorders. The energy consumption during both production and non-production periods of the machine is computed. The energy consumption in EPQ policies is contingent upon the production rate and the machine's states (off or standby) during non-production phases. Utilizing the proposed resolution algorithm, the model under examination seeks to minimize the average total system cost while considering the production rate, cycle time, the initial production time of the cycle, and the optimal machine state during non-production periods. To demonstrate the formulated model, a numerical analysis is conducted, with a particular focus on the impact of allowing backorders.
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