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The Constrained Single-Row Facility Layout Problem with Repairing Mechanisms

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Nature-Inspired Methods for Metaheuristics Optimization

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 16))

Abstract

The single-row facility layout problem (SRFLP), which deals with the placement of some facilities along a row by minimizing the overall material flow cost among them, is usually studied as an unconstrained problem allowing the placement of the facilities arbitrarily without any restriction. But a practical SRFLP instance may require to respect certain constraints imposed on the arrangement of its facilities. Such an SRFLP model, which can be termed as a constrained SRFLP (cSRFLP), is studied here by requiring to place some facilities in fixed locations, and/or in predefined orders with/without allowing the arrangement of any other facility in between two ordered facilities. The handling of such a complex problem generally requires a specialized algorithm incorporating some problem-specific information for intelligent search. But the development of an algorithm needs expertise, from which practitioners often suffer. Hence, it is shown here how the cSRFLP can be tackled using a general-purpose algorithm with some repairing mechanisms outside the algorithm for forcibly satisfying the constraints of the problem. Employing a permutation-based genetic algorithm for this purpose, the potentiality of the proposed procedure is demonstrated by applying it to a set of cSRFLP instances of different sizes.

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Correspondence to Dilip Datta .

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Kalita, Z., Datta, D. (2020). The Constrained Single-Row Facility Layout Problem with Repairing Mechanisms. In: Bennis, F., Bhattacharjya, R. (eds) Nature-Inspired Methods for Metaheuristics Optimization. Modeling and Optimization in Science and Technologies, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-030-26458-1_20

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  • DOI: https://doi.org/10.1007/978-3-030-26458-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26457-4

  • Online ISBN: 978-3-030-26458-1

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