Abstract
The allocation of buffers between workstations is a major optimization problem faced by manufacturing systems designers. It entails the determination of optimal buffer allocation plans in production lines with the objective of maximizing their throughput. We present and compare two stochastic approaches for solving the buffer allocation problem in large reliable production lines. The allocation plan is calculated subject to a given amount of total buffer slots using simulated annealing and genetic algorithms. The throughput is calculated utilizing a decomposition method.
Highlights
The allocation of buffers between workstations is a major optimization problem faced by manufacturing systems designers
We have evaluated different approaches for solving the optimal buffer allocation problem for large production lines, by performing the following steps: S1 We utilized the decomposition method [2] as an evaluative tool to determine the throughput of the lines
S2 To find the buffer allocation that maximizes the throughput of the line, we utilized two stochastic methods, simulated annealing and genetic algorithms, adapted for solving this problem
Summary
The allocation of buffers between workstations is a major optimization problem faced by manufacturing systems designers. It is a very complex task that must account for the random fluctuations in mean production rates of the individual workstations of the lines To solve this problem there is a need for two different tools. The second tool is a search (generative) method that tries to determine an optimal or near optimal value for the decision variables, which in our case are the buffer capacities of the intermediate buffer locations in the line. Examples of such methods are the classical search methods such as the well-known Hooke-Jeeves method, various heuristic methods, knowledge based methods, genetic algorithms, and simulated annealing
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