本研究應用粒子群最佳化演算法結合彈性區帶結構求解不等面積設施 佈置問題。提出多重粒子群最佳化演算法,分別改善設施填入順序、彈性區 帶寬度組合及彈性區帶個數。本研究以整數混合實數進行設施編碼。建構式 粒子群為改善設施填入順序,其為整數型態,故以最大速度法更新粒子之速 度與位置;改善式粒子群為多工粒子群,分別改善整數型態之彈性區帶數及 實數型態之彈性區帶寬度,因此,以最大速度法及慣性權重法更新粒子中之 區帶數與彈性區帶寬度組合。 本研究並以多重粒子群最佳化演算法與單一粒子群最佳化演算法進行 多組國際數值測詴例實驗,其求解結果發現,多重粒子群最佳化演算法之求 解品質遠高於單一粒子群最佳化演算法。而且多重粒子群最佳化演算法的求 解品質與Kulturel-Konak and Konak (2011b)之求解品質不相上下。
In this study, a new flexible bay structure representation and a particle swarm optimization containing multiple swarms (PSOMS) and are proposed to solve the unequal-area facility layout problem. An efficient method of coding the relevant features of a layout as a particle memory is an important requirement for applying PSO to the facility layout problem. A mixture coding which combines integer coding with real coding is proposed in this study. The symbols for the code of sequence lists of departments are integers between 1 and N, which represent departments. The same way is used to represent the number of bays. The symbols for the code of the bay width are real numbers between 0.0 and the area width. Several international benchmark problems are used to test the algorithm efficiency of PSOMS. The results are compared with the previously best known solutions. PSOMS can obtain the same or better solutions to some benchmark problems. These results show the potential for solving complex facility layout problems.
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