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A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand
Goli, Alireza1; Tirkolaee, Erfan Babaee2,3; Malmir, Behnam4; Bian, Gui-Bin5; Sangaiah, Arun Kumar6
Source PublicationCOMPUTING
ISSN0010-485X
2019-06-01
Volume101Issue:6Pages:499-529
Corresponding AuthorSangaiah, Arun Kumar(arunkumarsangaiah@gmail.com)
AbstractThis paper addresses a robust multi-objective multi-period aggregate production planning (APP) problem based on different scenarios under uncertain seasonal demand. The main goals are to minimize the total cost including in-house production, outsourcing, workforce, holding, shortage and employment/unemployment costs, and maximize the customers' satisfaction level. To deal with demand uncertainty, robust optimization approach is applied to the proposed mixed integer linear programming model. A goal programming method is then implemented to cope with the multi-objectiveness and validate the suggested robust model. Since APP problems are classified as NP-hard, two solution methods of non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective invasive weed optimization algorithm (MOIWO) are designed to solve the problem. Moreover, Taguchi design method is implemented to increase the efficiency of the algorithms by adjusting the algorithms' parameters optimally. Finally, several numerical test problems are generated in different sizes to evaluate the performance of the algorithms. The results obtained from different comparison criteria demonstrate the high quality of the proposed solution methods in terms of speed and accuracy in finding optimal solutions.
KeywordAggregate production planning Uncertain seasonal demand Multi-objective invasive weed optimization algorithm (MOIWO) NSGA-II Robust optimization
DOI10.1007/s00607-018-00692-2
WOS KeywordSUPPLY CHAIN ; OBJECTIVE OPTIMIZATION ; GENETIC ALGORITHM ; MODEL
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:000467041900002
PublisherSPRINGER WIEN
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24576
Collection中国科学院自动化研究所
Corresponding AuthorSangaiah, Arun Kumar
Affiliation1.Yazd Univ, Dept Ind Engn, Yazd, Iran
2.Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran
3.Islamic Azad Univ, Ayatollah Amoli Branch, Young Researchers & Elite Club, Amol, Iran
4.Univ Virginia, Dept Syst & Informat Engn, Charlottesville, VA 22904 USA
5.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
6.Vellore Inst Technol, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India
Recommended Citation
GB/T 7714
Goli, Alireza,Tirkolaee, Erfan Babaee,Malmir, Behnam,et al. A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand[J]. COMPUTING,2019,101(6):499-529.
APA Goli, Alireza,Tirkolaee, Erfan Babaee,Malmir, Behnam,Bian, Gui-Bin,&Sangaiah, Arun Kumar.(2019).A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand.COMPUTING,101(6),499-529.
MLA Goli, Alireza,et al."A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand".COMPUTING 101.6(2019):499-529.
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