A Novel Approach for Material Handling-Driven Facility Layout

被引:1
作者
Erik, Adem [1 ,2 ]
Kuvvetli, Yusuf [3 ]
机构
[1] Tarsus Univ, Project Off, Takbas Mahallesi Kartaltepe Sokak, TR-33400 Mersin, Turkiye
[2] Univ Iowa, Fac Ind & Syst Engn, Seamans Ctr Engn Arts & Sci 4627, Iowa City, IA 52240 USA
[3] Cukurova Univ, Fac Ind Engn, TR-01330 Adana, Turkiye
关键词
dynamic facility layout problem; genetic algorithm; simulated annealing; flexible bay structure; mixed integer non-linear programming; hybrid heuristics; GENETIC ALGORITHM; OPTIMIZATION; HEURISTICS;
D O I
10.3390/math12162548
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Material handling is a widely used process in manufacturing and is generally considered a non-value-added process. The Dynamic Facility Layout Problem (DFLP) considered in this paper minimizes the total material handling and re-arrangement cost. In this study, an integrated DFLP model with unequal facility areas, assignment of material handling devices (MHD), and flexible bay structure (FBS) is considered, and it is aimed to propose fast solution approaches. Two different solution methods are proposed for the problem, which are the genetic algorithm and the simulated annealing algorithm, respectively. In both methods, a non-linear mathematical model solution was used to calculate the fitness values. Thus, the solutions in the feasible solution space are utilized. The proposed solution approaches were applied to solve four problems published in the literature. The computational experiments have validated the effectiveness of the algorithms and the quality of solutions produced.
引用
收藏
页数:37
相关论文
共 71 条
[1]   Dynamic facilities planning model for large scale construction projects [J].
Al Hawarneh, Alaa ;
Bendak, Salaheddine ;
Ghanim, Firas .
AUTOMATION IN CONSTRUCTION, 2019, 98 :72-89
[2]  
Alamiparvin R., 2021, J. Qual. Eng. Prod. Optim, V6, P147
[3]   Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization [J].
Asl, Ali Derakhshan ;
Wong, Kuan Yew .
JOURNAL OF INTELLIGENT MANUFACTURING, 2017, 28 (06) :1317-1336
[4]   A dynamic multi-objective approach for the reconfigurable multi-facility layout problem [J].
Azevedo, Maria Manuela ;
Crispim, Jose Antonio ;
de Sousa, Jorge Pinho .
JOURNAL OF MANUFACTURING SYSTEMS, 2017, 42 :140-152
[5]  
Barzinpour F., 2019, J. Qual. Eng. Prod. Optim, V1, P11
[6]   Genetic algorithm-based community detection in large-scale social networks [J].
Behera, Ranjan Kumar ;
Naik, Debadatta ;
Rath, Santanu Kumar ;
Dharavath, Ramesh .
NEURAL COMPUTING & APPLICATIONS, 2020, 32 (13) :9649-9665
[7]   CF-GGA: a grouping genetic algorithm for the cell formation problem [J].
Brown, EC ;
Sumichrast, RT .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2001, 39 (16) :3651-3669
[8]  
Burke E. K., 2005, Search methodologies, DOI [10.1007/0-387-28356-0_6, DOI 10.1007/0-387-28356-0_6]
[9]  
De Jong K., 1988, Machine Learning, V3, P121, DOI 10.1023/A:1022606120092
[10]   AN INTEGRATED DYNAMIC FACILITY LAYOUT AND JOB SHOP SCHEDULING PROBLEM: A HYBRID NSGA-II AND LOCAL SEARCH ALGORITHM [J].
Erfani, Behrad ;
Ebrahimnejad, Sadoullah ;
Moosavi, Amirhossein .
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION, 2020, 16 (04) :1801-1834