由於消費者需求型態改變、企業產品相互競爭及科技進步發達，產品需求趨於多種少量、生命週期日短、訂單交期短促、行銷通道的阻隔及採購與生產全球化等，物流配送系統的效率，將會影響整個供應鏈體系的經營良窳，使得企業希望藉由改善製造與配送產品的流程，以增加邊際利潤和獲得競爭優勢。
本研究建構四階層多商品供應鏈間斷期配銷批量模型，包括有供應商、製造商、配銷中心及零售商，總成本包括運輸成本、訂購成本、存貨成本、製造成本，且運輸成本和運輸批量為不連續線性關係，零售商的需求為已知，求解模式中的各階成員的訂購量及其訂購對象以及製造商之製造量，並計算出各期各成員的存貨量，目標函數為總成本最小。
在模式解法上，由於模式中具有大量0、1變數及非線性的限制式，當問題規模變大時，解空間呈指數增加，使用傳統最佳化方法求解顯得較無效率，因此本研究利用基因演算法為基礎加以修改並求解本研究數學模式，並以LINGO軟體求解本研究數學模式，並將二者所得到的解和求解時間加以比較，以驗證本研究演算法之效率。在演算法之參數設定方面，以四個因子分成三個水準在四個例題上加以實驗。
綜合本研究之實驗測試結果可以得到以下結論：由參數分析中可知本研究啟發式演算法在交配率為0.9及突變率為0.01及群數為40時得到的解比其它參數水準的所求的解佳，在執行代數方面代數越大則所求的解越佳。本研究啟發式演算法測試10個例題，最大期數為六期，例題中規模較小例題可求得最佳解，在規模較大的例題中也可以求得品質不錯的解，可見本研究之啟發解有著不錯的求解品質。在求解時間方面，因著本研究之數學模式複雜，且是非線性模式，由實驗得知以基因演算法為基礎之啟發式演算法較最佳解所花費時間相對的縮短很多。

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