A mathematical model and a parallel multiple search path simulated annealing for an integrated distributed layout design and machine cell formation

- Developed a model for an integrated distributed layout and machine cell formation.
- Illustrate model applicability along the spectrum of stable and volatile demand patterns.
- Developed an efficient simulated annealing.
- Implement the developed algorithm in a parallel computing environment.

Facility layout problem is a well-researched problem of finding configurations of departments and machines on a plant floor with the objective of improving material handling efficiency. With this objective, different techniques of configuring facilities have been documented in literature. Among them are cellular and distributed layouts. Cellular layouts are applicable in scenarios where demand and product mix are relatively stable and rational part families/machine cells can be identified. With this assumption, the literature provides many techniques for their design. Distributed layout, on the other hand, are recommended in volatile environments where product demand and mix are changing very rapidly. However, we argue that a real-life scenario may lay within the spectrum of these two extremes. In this paper, we attempt to bridge this gap by developing a mathematical model that integrates distributed layout design and machine cell formation with an objective to minimize a weighted sum of material handling and inter cellular movement costs. Through distributing the machines over the shop floor, the model attempts to minimize material handling cost. By identifying possible machine cells and part families, it attempts to minimize inter cellular movements. At the same time, the model ensures that machines that belong to the same cell are laid out on contiguous physical locations so that the advantages of cellular manufacturing systems can be fully exploited. Operations sequence, alternative routing, workload balancing among cells and other pragmatic issues are also incorporated in the model. We developed a parallel multiple search path simulated annealing to solve the proposed model efficiently. Several numerical examples are presented to illustrated the model and the computational performance of the developed algorithm.