A hybrid ant colony algorithm for Job Shop Scheduling Problem

被引：0

作者：

Chen, Xuefang ^{[1
]}

Zhu, Qiong ^{[1
]}

Zhang, Jie ^{[1
]}

机构：

[1] Suzhou Vocat Univ, Dept Elect Mech Engn, Suzhou 215104, Jiangsu, Peoples R China

来源：

PROCEEDING OF THE SEVENTH INTERNATIONAL CONFERENCE ON INFORMATION AND MANAGEMENT SCIENCES | 2008年 / 7卷

关键词：

ant system; max-min Ant System; elitist strategy; dynamic parameter control; job shop scheduling;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Job Shop Scheduling Problem (JSSP) is one of the NP-hard problems. JSSP has been investigated from a variety of perspectives resulting in several techniques combining heuristic as well as problem specific strategies. A hybrid Ant Colony Algorithm (HACA) is proposed which is derived from the existing methods, in the mean time, dynamic parameter control mechanism is adopted with a dividable parameter 8 which gives a new variable to control the computational rate of ant algorithm. The procedure of using HACA to solve JSSP can be divided into 3 phases, i.e. prophase, metaphase and anaphase- Each phase adopts special pheromone release method and transition probability expression. The results obtained from experimental evaluation oil JSSP shows that HACA strongly enhance the computational and convergent rate of basic Ant System algorithm.

引用

页码：575 / 579

页数：5

共 50 条

[21] Dynamic Job Shop Scheduling Problem With New Job Arrivals Using Hybrid Genetic Algorithm [J].

Ben Ali, Kaouther ;

Bechikh, Slim ;

Louati, Ali ;

Louati, Hassen ;

Kariri, Elham .

IEEE ACCESS, 2024, 12 :85338-85354

[22] Hybrid Rollout Approaches for the Job Shop Scheduling Problem [J].

Guerriero, F. .

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2008, 139 (02) :419-438

[23] An improved artificial bee colony algorithm for fuzzy flexible job-shop scheduling problem [J].

Zheng X.-C. ;

Gong W.-Y. .

Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2020, 37 (06) :1284-1292

[24] Hybrid Rollout Approaches for the Job Shop Scheduling Problem [J].

F. Guerriero .

Journal of Optimization Theory and Applications, 2008, 139 :419-438

[25] Artificial bee colony algorithm for solving a bi-objective job shop scheduling problem [J].

Zhang R. .

Advances in Information Sciences and Service Sciences, 2011, 3 (08) :319-326

[26] Genetic algorithm application on the job shop scheduling problem [J].

Wu, CG ;

Xing, XL ;

Lee, HP ;

Zhou, CG ;

Liang, YC .

PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, :2102-2106

[27] A sequence list algorithm for the job shop scheduling problem [J].

Zhang, Shuli .

Open Electrical and Electronic Engineering Journal, 2013, 7 (SPEC ISS 1) :55-61

[28] A Parallel Genetic Algorithm for the Job Shop Scheduling Problem [J].

Nguyen Huu Mui ;

Vu Dinh Hoa ;

Luc Tri Tuyen .

2012 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT), 2012, :19-24

[29] A hybrid genetic algorithm for the job shop scheduling problems [J].

Tao, Z ;

Xie, LY ;

Hao, CZ .

PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1 AND 2: INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT IN THE GLOBAL ECONOMY, 2005, :335-339

[30] The hybrid heuristic genetic algorithm for job shop scheduling [J].

Zhou, H ;

Feng, YC ;

Han, LM .

COMPUTERS & INDUSTRIAL ENGINEERING, 2001, 40 (03) :191-200

← 1 2 3 4 5 →