近年來，供應鏈管理已經成為許多學術界和業界人士感興趣的一個重要主題。本文主要探討安排兩階段供應鏈的協調問題，且專注於生產與運輸兩方面，第一階段包含 個擁有不同生產速度的供應商，第二階段是由 輛具有不同速度和運輸能力的車輛所構成，而由第一階段供應商所產出的產品皆有不同的大小體積。本研究的主要目標是使最大完成時間最小化。該問題已被建構成一個繁雜的整數規劃問題，且曾使用性別遺傳算演算法來求解。由於本研究為 NP-hard的問題，故我們將提出一個新的啟發式演算法與結合類電磁式演算法來解決此問題。我們將性別遺傳算演算法與啟發式演算法結合類電磁式演算法進行相同的實驗，由實驗結果可得知，啟發式演算法結合類電磁式演算法不但減少計算時間成本，並且得到較佳的解。

In recent years, supply chain management (SCM) has become an important subject that is of interest to many researchers and practitioners. This paper considers the scheduling of a two-stage supply chain coordination and focuses on the aspect of production and transportation. The first stage contains suppliers with various production speeds while the second stage is composed of vehicles, each of which may have a different speed and transport capacity. It is assumed that the various output products have different sizes. The primary objective of this study is to minimize the maximum completion time for all jobs. This NP-hard problem had been modeled as a mixed integer programming problem and a gendered genetic algorithm (GGA) was used to search good solutions. In this paper, a new heuristic is proposed and an electromagnetism-like algorithm (EM) is developed to solve the problem. Then, the performance and results of EM and GGA for solving the problem are analyzed and compared. Computational results show that the proposed EM algorithm achieves better performance than the existing GGA in that EM requires much less computation time.

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