文章詳目資料
Journal of Computers EIMEDLINEScopus
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| 篇名 | Applications of an Improved PSO in Integer Linear Programming |
|---|---|
| 卷期 | 32:6 |
| 作者 | Ying Wang |
| 頁次 | 098-106 |
| 關鍵字 | improved PSO 、 integer programming 、 penalty function 、 stochastic solution 、 EI 、 MEDLINE 、 Scopus |
| 出刊日期 | 202112 |
| DOI | 10.53106/199115992021123206008 |
中文摘要
英文摘要
In order to address the problems with production planning for Model Q cars and Model X new energy cars of an automotive group, a mathematical model is proposed, which is intended for a constrained integer linear programming problem. An AI algorithm, i.e. PSO, is introduced to solve this problem, while such methods as penalty function are used to solve the constraint conditions and integer programming problem. Furthermore, in order to overcome the challenge that the standard PSO is very likely to meet a local extremum, an improved PSO is proposed, which, as shown in terms of search computing results, is more accurate and efficient than the standard PSO, thus aptly solving the integer linear programming problem.
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