A genetic algorithm approach to the machine-component grouping problem with multiple objectives
Computers and Industrial Engineering
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Facilities layout design by genetic algorithms
ICC&IE Selected papers from the 22nd ICC&IE conference on Computers & industrial engineering
A hybrid optimization approach for layout design of unequal-area facilities
Computers and Industrial Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A simulated annealing algorithm for dynamic layout problem
Computers and Operations Research
An improved genetic algorithm for facility layout problems having inner structure walls and passages
Computers and Operations Research
An ant algorithm for the single row layout problem in flexible manufacturing systems
Computers and Operations Research
A genetic algorithm for facility layout problems of different manufacturing environments
Computers and Industrial Engineering
Computers and Operations Research
Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm
Computers and Industrial Engineering
A new mixed integer programming formulation for facility layout design using flexible bays
Operations Research Letters
Multiobjective layout optimization of robotic cellular manufacturing systems
Computers and Industrial Engineering
Determination of the locations and capacities of sugar cane loading stations in Thailand
Computers and Industrial Engineering
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Facilities location problem deals with the optimization of location of manufacturing facilities like machines, departments, etc. in the shop floor. This problem greatly affects performance of a manufacturing system. It is assumed in this paper that there are multiple products to be produced on several machines. Alternative processing routes are considered for each product and the problem is to determine the processing route of each product and the location of each machine to minimize the total distance traveled by the materials within the shop floor. This paper presents a mixed-integer non-linear mathematical programming formulation to find optimal solution of this problem. A technique is used to linearize the formulated non-linear model. However, due to the NP-hardness of this problem, even the linearized model cannot be optimally solved by the conventional mathematical programming methods in a reasonable time. Therefore, a genetic algorithm is proposed to solve the linearized model. The effectiveness of the GA approach is evaluated with numerical examples. The results show that the proposed GA is both effective and efficient in solving the attempted problem.