Using Iterated Greedy with a New Population Approach for the Flexible Job-shop Scheduling Problem

被引：0

作者：

Al Aqel, G. ^{[1
]}

Li, X. ^{[1
]}

Gao, L. ^{[1
]}

Gong, W. ^{[2
]}

Wang, R. ^{[3
]}

Ren, T. ^{[4
]}

Wu, G. ^{[5
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan, Hubei, Peoples R China

[2] China Univ Geosci, Sch Comp Sci, Wuhan, Hubei, Peoples R China

[3] Natl Univ Def Technol, Coll Syst Engn, Changsha, Hunan, Peoples R China

[4] Cent South Univ Forestry & Technol, Sch Transportat & Logist, Changsha, Hunan, Peoples R China

[5] Cent S Univ, Sch Traff & Transportat Engn, Changsha, Hunan, Peoples R China

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEE IEEM) | 2018年

基金：

中国国家自然科学基金;

关键词：

Flexible Job-shop Scheduling Problem; Iterated Greedy; Telescopic Population; HEURISTIC ALGORITHM; PERFORMANCE; FLEXIBILITY; MACHINE;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The flexible job-shop scheduling problem (FJSP) is known as an important problem in manufacturing systems. Many methods have been proposed to solve this problem. The iterated greedy (IG) is one of those algorithms that are widely used in simpler shop scheduling problems. This research proposes a new Telescopic Population approach (TP) to assist the IG in solving the FJSP. The use of TP approach with IG provides an effective method that is also easier to reproduce. The performance of TP with IG proves that the new population approach effectively improves the performance of IG.

引用

页码：1235 / 1239

页数：5

共 22 条

[1] Analyzing the effect of dispatching rules on the scheduling performance through grammar based flexible scheduling system [J].

Baykasoglu, Adil ;

Ozbakir, Lale .

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2010, 124 (02) :369-381

[2]

Brandimarte P., 1993, Annals of Operations Research, V41, P157, DOI 10.1007/BF02023073

[3] JOB-SHOP SCHEDULING WITH MULTIPURPOSE MACHINES [J].

BRUCKER, P ;

SCHLIE, R .

COMPUTING, 1990, 45 (04) :369-375

[4] Solving the Flexible Job Shop Scheduling Problem With Makespan Optimization by Using a Hybrid Taguchi-Genetic Algorithm [J].

Chang, Hao-Chin ;

Chen, Yeh-Peng ;

Liu, Tung-Kuan ;

Chou, Jyh-Horng .

IEEE ACCESS, 2015, 3 :1740-1754

[5] Evaluation of mathematical models for flexible job-shop scheduling problems [J].

Demir, Yunus ;

Isleyen, S. Kursat .

APPLIED MATHEMATICAL MODELLING, 2013, 37 (03) :977-988

[6] Mathematical modeling and heuristic approaches to flexible job shop scheduling problems [J].

Fattahi, Parviz ;

Mehrabad, Mohammad Saidi ;

Jolai, Fariborz .

JOURNAL OF INTELLIGENT MANUFACTURING, 2007, 18 (03) :331-342

[7] A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion [J].

Gao, Kai Zhou ;

Suganthan, Ponnuthurai Nagaratnam ;

Chua, Tay Jin ;

Chong, Chin Soon ;

Cai, Tian Xiang ;

Pan, Qan Ke .

EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (21) :7652-7663

[8] An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem [J].

Li, Xinyu ;

Gao, Liang .

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2016, 174 :93-110

[9] Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems [J].

Minella, Gerardo ;

Ruiz, Ruben ;

Ciavotta, Michele .

COMPUTERS & OPERATIONS RESEARCH, 2011, 38 (11) :1521-1533

[10]

Muthiah A, 2016, 2016 INTERNATIONAL CONFERENCE ON ENERGY EFFICIENT TECHNOLOGIES FOR SUSTAINABILITY (ICEETS), P896, DOI 10.1109/ICEETS.2016.7583875

← 1 2 3 →