Mathematical Modeling and Genetic Algorithms for Product Sequencing in a Cellular System

Author:

Süer Gürsel A.1,Yarimoglu Fatih1

Affiliation:

1. Ohio University, USA

Abstract

This chapter considers a product-sequencing problem in a synchronized manufacturing environment, which is using a uniform time bucket approach for synchronization. This problem has been observed in a jewelry manufacturing company and is valid in other labor-intensive cellular environments. The scheduling problem handled has two aspects: first, determining manpower allocation; second, sequencing the products in order to minimize the number of periods where available manpower is exceeded. The number of operators needed in a time bucket may exceed the available manpower level as different products have different manpower requirements for different processes. A mathematical model is developed for the manpower allocation part of the problem. To perform product sequencing, two methods are used, namely mathematical modeling and genetic algorithm. A new five-phase GA approach is proposed, and the results show that it outperforms the classical GA. Several experiments have been conducted to find better GA parameters as well. Finally, GA results are compared with mathematical model results. Mathematical Modeling finds optimal result in a reasonable time for small problems. On the other hand, for the bigger problems, genetic algorithm is a feasible approach to use.

Publisher

IGI Global

Reference23 articles.

1. Babayigit, C. (2003). Genetic algorithms and mathematical models in manpower allocation and cell loading problem. (MS Thesis). Ohio University, Athens, OH.

2. Escobar, P. (2003). A concurrent design of a period batch control system by genetic algorithm. Columbus, OH: Group Technology/Cellular Manufacturing World Symposium.

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