Solving Scheduling Problems with Genetic Algorithms Using a Priority Encoding Scheme

被引：0

作者：

Subirats, Jose L. ^{[1
]}

Mesa, Hector ^{[1
]}

Ortega-Zamorano, Francisco ^{[2
]}

Juarez, Gustavo E. ^{[3
]}

Jerez, Jose M. ^{[1
]}

Turias, Ignacio ^{[4
]}

Franco, Leonardo ^{[1
]}

机构：

[1] Univ Malaga, Dept Comp Sci, Malaga, Spain

[2] Yachay Tech, Sch Math & Comp Sci, San Miguel De Urcuqui, Ecuador

[3] Univ Nacl Tucuman, Fac Ciencias Exactas & Tecnol, San Miguel De Tucuman, Tucuman, Argentina

[4] Univ Cadiz, Dept Comp Sci, Cadiz, Spain

来源：

ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT I | 2017年 / 10305卷

关键词：

Evolutionary and genetic algorithms; Job shop problems; Priority encoding scheme;

D O I：

10.1007/978-3-319-59153-7_5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Scheduling problems are very hard computational tasks with several applications in multitude of domains. In this work we solve a practical problem motivated by a real industry situation, in which we apply a genetic algorithm for finding an acceptable solution in a very short time interval. The main novelty introduced in this work is the use of a priority based chromosome codification that determines the precedence of a task with respect to other ones, permitting to introduce in a very simple way all problem constraints, including setup costs and workforce availability. Results show the suitability of the approach, obtaining real time solutions for tasks with up to 50 products.

引用

页码：52 / 61

页数：10

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