The multi-period stochastic plant layout problem

Plant layout is a problem that involves the assignment of different facilities to different sites. Existing models in plant layout failed to incorporate the stochastic nature of the workflow between facilities and budget constraints on re-layout downtime and transfer cost in the general structure of...

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Bibliographic Details
Main Author: Seva, Rosemary R.
Format: text
Language:English
Published: Animo Repository 1993
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Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/1522
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Institution: De La Salle University
Language: English
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Summary:Plant layout is a problem that involves the assignment of different facilities to different sites. Existing models in plant layout failed to incorporate the stochastic nature of the workflow between facilities and budget constraints on re-layout downtime and transfer cost in the general structure of the model. The model of Rosenblatt and Kropp (1992) assumed stochastic nature of the workflow between facilities for a single period in the solution process only. On the other hand, Balakrishnan, Jacobs and Venkataramanan (1992), assumed that the workflow between facilities is uniformly distributed in the new solution process they introduced on the constrained dynamic plant layout problem. In this study, a constrained multi-period model was formulated incorporating the stochastic nature of the workflow between facilities in the general model and considering transfer and downtime cost constraints. The model was initially formulated using Quadratic Assignment Problem (QAP) but the convexity was not proven using classical optimization. The model was formulated anew using integer linear programming. Since the model was linear the convexity was assured. The model was solved using MILP88 and an optimal solution was obtained for a two-period three-site and three-facility problem. The study proved that important costs in plant layouting such as material handling, set-up and re-layout downtime and transfer costs can be incorporated in one model and that it can be solved optimally using integer linear programming.