A New Efficient Encoding Mode of Genetic Algorithms for the Generalized Plant Allocation Problem

This study proposes a novel, efficient means of encoding genetic algorithms to solve the generalized plant allocation problem. The problem relates to allocating products across plants to minimize a total cost function. The proposed encoding method can reduce the search space of solutions more efficiently than the penalty encoding method does. The new encoding method thus exhibits higher performance. It need involve only a few more generations to yield sufficiently good solutions when the number of plants is increased. The penalty encoding method, however, requires many more generations to yield the same solutions. Additionally, a new simultaneous crossover and mutation operation is proposed to enable the new method of encoding chromosomes to run correctly following standard genetic algorithm procedures. In addition to the mathematical certification, the performance of this approach is evaluated using some test problems of various sizes. Solutions obtained by this approach are always efficient.

並列關鍵字

genetic algorithms ； efficient encoding scheme ； plant allocation ； combinatorial optimization problems ； penalty encoding

被引用紀錄

高淑娟（2008）。應用變動鄰域搜尋法於資源分配問題之研究〔碩士論文，元智大學〕。華藝線上圖書館。https://doi.org/10.6838/YZU.2008.00197

Wang, Y. C. (2010). 含作業員選配的組裝線平衡問題及其蟻拓求解方法 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2010.01824

簡家貴（2016）。分析及建立以標竿學習規劃為導向之供應商評選機制〔碩士論文，逢甲大學〕。華藝線上圖書館。https://doi.org/10.6341/fcu.M0362015

莊佳穎（2009）。變動鄰域搜尋法於多目標資源分配問題之研究〔碩士論文，元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-2207200912200200

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A New Efficient Encoding Mode of Genetic Algorithms for the Generalized Plant Allocation Problem

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