Solving the Economic Lot and Inspection Scheduling Problem using the Extended Basic Period approach under Power-of-Two policy

Abstract

The focus of this study is to solve the Economic Lot and Inspection Scheduling Problem (ELISP) using the Extended Basic Period (EBP) approach under Power-of-Two (PoT) policy. The objective of the ELISP is to determine an optimal cycle time and an optimal production and inspection schedule so as to minimize the total cost per unit time. Under PoT policy, we formulate a mathematical model by taking into account the constraints for both production and inspection capacities. Also, we propose a Hybrid Genetic Algorithm (HGA) which is equipped with a search algorithm that not only seeks to improve solution quality, but also assures a feasible solution for each chromosome obtained from the evolutionary processes. Our numerical experiments show that the proposed HGA effectively solves the ELISP using the EBP approach, and its solutions outperform the solutions from the ELISP using the Common Cycle approach.

本研究主要運用延伸基本週期法在二幂策略下求解經濟批量與檢驗排程問題 (Economic Lot and Inspection Scheduling Problem, ELISP)。 本論文所提之 ELISP 數學模式是傳統經濟批量排程問題的延伸研究。 本模式的目的是決定基本週期、 各產品的週期乘數與各產品之檢驗次數的最佳組合 ， 最小化單位時間總成本。 本文所提之 ELISP 數學模式將生產產能與檢驗產能列入限制條件 ， 主要假設為產品生產後必須進行全數檢驗。 本研究運用遺傳演算法、 搜尋演算法與可行解測試法 ， 提出一個四階段求解程序來求得近似最佳解。 本研究並以一個十項產品範例與隨機實驗 ， 驗證本模式及所提出的四階段求解程序為求解經濟批量與檢驗排程問題的一個有效的研究方法。

(*聯絡人: [email protected])

Keywords:

• lot
• production
• inspection
• scheduling
• Genetic Algorithm
• Power-of-Two

Keywords:

• 關鍵詞 ： 生產批量 ； 檢驗 ； 排程 ； 遺傳演算法 ； 二幂策略

Acknowledgments

This research was supported by National Science Council, Taiwan, Republic of China, under Contract NSC-97-2221-E-029-016-MY2.

Notes

(*聯絡人: [email protected])