A Dynamic Programming Algorithm for Facility Location and Allocation

Curry, Guy L.; Skeith, Ronald W.

doi:10.1080/05695556908974424

Cited by 18 publications

(2 citation statements)

References 3 publications

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“…Specifically, either dynamic programming (Curry and Skeith 1969), branch and bound (Revelle and Swain 1970), heuristic method (Ignizio 1971,Shannon andIgnizio 1970)or mathematical modelling (Panneerselvam, et al 1990b) can be used to solve this problem. Since the problem is combinatorial in nature, the heuristic procedure developed by Ignizio (Ignizio 1971,Shannon andIgnizio 1970)is generally used.…”

Section: Warehouse Location Problemmentioning

confidence: 99%

Covering technique-based algorithm for machine grouping to form manufacturing cells

Balasubramanian

Panneerselvam

1993

International Journal of Production Research

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This paper discusses an algorithm which helps the formation. of machine groups (manufacturing cells). For a given set of components and their process routeing, the algorithm first considers several possible cells.It then developes a similarity matrix to reflect the components' routeing similarity with that of the arrangement of the facilities in the cell. In this paper, the heuristic procedure for solving the 'covering problem' has been modified to determine an economical number of manufacturing cells and cell arrangements (sequences of machines) so that each cell is identified to process specific component(s). The design process considered minimizing the total cost which includes handling, machines idle time and overtime. The algorithm has been applied to a practical case problem and its results are presented with a sensitivity analysis. I. IntroductionFacilities design has always been an important manufacturing systems activity in the past and the present. In the past it included the computation of facilities requirements followed by the design of a layout for the facilities. The layout design problems always considered some form of material handling criterion. It also usually started with a quantitative approach and very quickly reached a state when the designer's intuition and experience, as well as broadly acceptable norms of industrial facilities design such as functional or product oriented layout designs, were used to complete the design process.In recent times the ability to handle extended algorithmic types of design approaches using computers, and increased knowledge about group technology and cellular manufacturing concepts have motivated the facility designers to extend the design analysis closer to the final phase where intuition and experience played a major role in the past. The traditional view of the layout problem as a standard functional layout or a product layout is fast disappearing. The increasing awareness of just-intime concepts and flexible manufacturing systems focuses towards the design of cells of manufacturing machines. Such cells aim to include as many of the required facilities in a required sequence to facilitate smooth flow ofthe production of several components. It also aims to avoid excessive idleness of the facilities. Usually the designer faces a tradeoff situation between materials flow criterion and the facilities utilization criterion.

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Section: Warehouse Location Problemmentioning

confidence: 99%

Covering technique-based algorithm for machine grouping to form manufacturing cells

Balasubramanian

Panneerselvam

1993

International Journal of Production Research

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“…Schneider and Symons [ 381, and Whitaker [ 521, among others, adds to P3 the constraint that at least one facility must be located within s distance units of each community. P3 can be modified to incorporate the maximum distance constraint by letting N , = { j : d , I s}; the value of a,, in P3 is then given as follows:Notice, with the maximum distance constraint, for a feasible solution to exist, K must be sufficiently large to satisfy the maximum distance constraint.Exact solutions to P3 have been obtained by Curry and Skeith[5] using dynamic programming, by Jarvinen, et al…”

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confidence: 99%

On Covering Problems and the Central Facilities Location Problem

White

Case

1974

Geographical Analysis

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A number of variations of facilities location problems have appeared in the research literature in the past decade. Among these are problems involving the location of multiple new facilities in a discrete solution space, with the new facilities located relative to a set of existing facilities having known locations. In this paper a number of discrete solution space location problems are treated. Specifically, the covering problem and the central facilities location problem are shown to be related. The covering problem involves the location of the minimum number of new facilities among a finite number of sites such that all existing facilities (customers) are cooered by at least one new facility. The central facilities location problem consists of the location of a given number of new facilities among a finite number of sites such that the sum of the weighted distances between existing facilities and new facilities is minimized. Computational experience in using the same heuristic solution procedure to solve both problems is provided and compared with other existing solution procedures.

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Multi-purpose system for plant layout design

Hosni¹

1978

Computers & Industrial Engineering

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A Dynamic Programming Algorithm for Facility Location and Allocation

Cited by 18 publications

References 3 publications

Covering technique-based algorithm for machine grouping to form manufacturing cells

Covering technique-based algorithm for machine grouping to form manufacturing cells

On Covering Problems and the Central Facilities Location Problem

Multi-purpose system for plant layout design

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