Wyniki wyszukiwania - Biblioteka Nauki

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: dissimilarity measure

Sortuj według:

Ogranicz wyniki do:

THE MEASUREMENT OF THE ECONOMIC DISTANCE ON THE BASIS OF SYMBOLIC DATA

100%

Wilk J.

Acta Universitatis Lodziensis. Folia Oeconomica

2014

tom 3

nr 302

The economic distance defines a dissimilarity level between objects functioning in the economic space. It is one of the most important issues of spatial econometrics. However its measurement is difficult due to the definition, description and estimation problems. The objective of the paper is to indicate the role of symbolic data in describing the economic distance and also the way of its measurement using symbolic data analysis methods. A significance of the economic distance, measurement problems, symbolic data concept and dissimilarity measures, and also an empirical example were presented in the paper.

A hybrid heuristic based clustering algorithm to design manufacturing cell

51%

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

Management and Production Engineering Review

2010

tom Vol. 1, No. 4

26-37

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.