Hybridization of Genetic Algorithm and Linear Programming for Solving Cell Formation Problem with Alternative Process Routings

Shahrooz Shahparvari, Payam Chiniforooshan
unpublished
In this paper, a mathematical model is proposed to solve cell formation problem considering alternative process routings in which more than one process route for each part can be selected. The model attempts to minimize intercellular movements and incorporates several real-life production factors and practical constraints. In order to increase the flexibility provided by the multiplicity of routings, the model distributes production volume of each part among alternative routes. Also, a
more » ... s. Also, a constraint enforcing work load balancing among machines is included in the model. Due to the complexity and combinatorial nature of this model, an enhanced algorithm comprised of a genetic algorithm (GA) and a linear programming (LP) is proposed for solving the model. At each iteration, the algorithm identifies the machine cells by GA. Consequently, the production quantity of each part in each route is determined by LP sub-problem. A numerical example is solved and compared with the solution approach from the literature that selects only one route for each part. The computational results show that the proposed approach offers better solution.
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