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1

A tabu search algorithm for the cell formation problem with part machine sequencing

Papaioannou G., Wilson J. M.

Foundations of Computing and Decision Sciences

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2012

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Vol. 37, No. 2

97--127

EN

This paper presents extensions of the IP model where part-machine assignment and cell formation are addressed simultaneously and part machine utilisation is considered. More specifically, an integration of inter-cell movements of parts and machine set-up costs within the objective function, and also a combination of machine set-up costs associated with parts revisiting a cell when the part machine operation sequence is taken into account are examined and an enhanced model is formulated. Based upon this model’s requirements, an initial three stage approach is proposed and a tabu search iterative procedure is designed to produce a solution. The initial approach consists of the allocation of machines to cells, the allocation of parts to machines in cells and the evaluation of the objective function’s value. Special care has been taken when allocating parts to machine cells as part machine operation sequence is preserved making the system more complex but more realistic. The proposed tabu search algorithm integrates short term memory and an overall iterative searching strategy where two move types, single and exchange, are considered. Computational experiments verified both the algorithm’s robustness where promising solutions in reasonably short computational effort are produced and also the algorithm’s effectiveness for large scale data sets.

2

A hybrid heuristic based clustering algorithm to design manufacturing cell

Ghosh T., Sengupta S., Dan P. K.

Management and Production Engineering Review

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2010

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Vol. 1, No. 4

26-37

EN

The manufacturing cell formation problem consists of designing a subclass of machine cells and their corresponding part families with an objective to minimize the inter-cell and intracell moves of the items while enhancing the machine utilization. This paper demonstrates a hybrid heuristic algorithm namely HACCF (Heuristic based Agglomerative Clustering for Cell Formation) exploiting the centroid linkage clustering method and the Minkowski distance metric as dissimilarity coeffcient. An exhaustive heuristic technique is developed and combined with the proposed clustering method to form manufacturing cells. 15 widely practiced datasets are obtained from past literature and tested with the proposed technique. The computational results are exhibited using the grouping efficacy as performance measure for the abovementioned test problems. The proposed technique is shown to outperform the standard and published techniques such as ZODIAC, GRAFICS, TSP based genetic algorithm and simple genetic algorithm and attained 73.33% improved result by exceeding the solution quality on the test problems. Therefore the proposed technique could be extensively used and could be hybridized with intelligent approaches to obtain more improved result in the vicinity of future cellular manufacturing system.

3

Machine-part grouping and cluster analysis: similarities, distances and grouping criteria

Owsiński J.W.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2009

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Vol. 57, nr 3

217-228

EN

The paper considers the machine-part grouping problem, as equivalent to partitioning the set of machines and operations into subsets, corresponding to block diagonalisation with constraints. The attempts to solve the problem with clustering methods are outlined. The difficulties encountered are presented, related to (i) ambiguity of formulations; (ii) selection of criteria; and (iii) lack of effective algorithms. These are illustrated in more detail with a limited survey of similarity and distance definitions, and of criteria used, constituting the main body of the paper. The return is proposed to the basic paradigm of cluster analysis, as providing simple and fast algorithms, which, even if not yielding optimal solutions, can be controlled in a simple manner, and their solutions improved.