Abstract: This paper presents a new approach to the scheduling of manufacturing cells which have flow-shop configuration. The approach is based on the genetic algorithm, which is a meta-heuristic for solving combinatorial optimization problems. The performance measure demonstrated in this paper is the optimization of the mean flow time. The procedure developed automatically computes the make-span. A flexible manufacturing cell schedule is used as a case study. The genetic algorithm procedure was used to solve a published data set for simple scheduling problems. The genetic algorithm procedure was further used to solve large flow-shop scheduling problems having machine sizes of up to 30 and job sizes of up to 100 in very reasonable computati...
This paper presents a methodology to solve the manufacturing cell creation and the production schedu...
Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing t...
There are different suggested values to adapt the basic parameters of a Genetic Algorithm, however...
The article is to present the application of genetic algorithm in production scheduling in a product...
In this paper, an approach using the concept of genetic algorithms is proposed as a powerful but sim...
This project presents a different approach by using genetic algorithm conducted to compare the work ...
Effective solutions to the cell formation and the production scheduling problems are vital in the de...
This paper considers the problem of scheduling part families and jobs within each part family in a f...
Minicells are small manufacturing cells dedicated to an option family and organized in a multi-stage...
Genetic Algorithm (GA) has been widely used for optimizing the flow shop scheduling problem due to i...
This work was aimed for developing computational intelligence for scheduling a manufacturing cell's ...
In the flexible manufacturing system, a reasonable production scheduling is crucial in shortening th...
This paper focuses on makespan minimization for the flow line scheduling problem using a Fuzzy Cell ...
In today’s competitive business world, manufacturers need to accommodate customer demands with appro...
In this paper, a novel genetic algorithm (GA) is proposed to solve the two-objective shop scheduling...
This paper presents a methodology to solve the manufacturing cell creation and the production schedu...
Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing t...
There are different suggested values to adapt the basic parameters of a Genetic Algorithm, however...
The article is to present the application of genetic algorithm in production scheduling in a product...
In this paper, an approach using the concept of genetic algorithms is proposed as a powerful but sim...
This project presents a different approach by using genetic algorithm conducted to compare the work ...
Effective solutions to the cell formation and the production scheduling problems are vital in the de...
This paper considers the problem of scheduling part families and jobs within each part family in a f...
Minicells are small manufacturing cells dedicated to an option family and organized in a multi-stage...
Genetic Algorithm (GA) has been widely used for optimizing the flow shop scheduling problem due to i...
This work was aimed for developing computational intelligence for scheduling a manufacturing cell's ...
In the flexible manufacturing system, a reasonable production scheduling is crucial in shortening th...
This paper focuses on makespan minimization for the flow line scheduling problem using a Fuzzy Cell ...
In today’s competitive business world, manufacturers need to accommodate customer demands with appro...
In this paper, a novel genetic algorithm (GA) is proposed to solve the two-objective shop scheduling...
This paper presents a methodology to solve the manufacturing cell creation and the production schedu...
Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing t...
There are different suggested values to adapt the basic parameters of a Genetic Algorithm, however...