Facility Location





Facility Location

In the article Facility Location Under Uncertainty written by Lawrence Snyder, the author is able to articulate the various concerns associated with establishment of new plants, distribution centers, and warehouses by organisation. The selection of such locations is marked by various challenges such as ensuring minimal costs, lead-time for consumers, transportation needs, infrastructure, and other basic inputs.

Source of Uncertainty

Some of the primary sources of uncertainty include costs, travel times, demand for goods and services and capacities for handling supply needs by an organization. Customer demand is considered an important factor towards determination of facility location. It is highly uncertain because it is primarily influenced by market trends. It adheres to ambiguous or normal distributions. Location capacity is also another uncertain factor in the selection of facility. It is relative to exchange rate uncertainties given that this is relative to financing aspects of a facility from phases such as construction to operations.

Capacity and associated costs vary from one region to another hence the considerations of global exchange rates as a primary determinant on the overall expenses of establishment of operations in a given region. Travel times are also important variables given that they influence movement of goods and access of services. Transport is seen as an important determinant in selection of facility location given that it plays a critical role in relation to efficiency and effectiveness in access and delivery of goods for the consumers.

In addition, this also influences the coat associated with movement of goods and the overall lead-time for consumers. In addition, demand is another concern that is marked by high levels of uncertainty given the associated with ambiguous or normal distributions within supply chains. Customer demand for goods and services in turn influences the appropriate levels of lead-time in terms of service or product delivery to the consumers. Furthermore, capacity concerns are also relative to demand needs and may vary from one location to another. Costs associated with different capacity levels for facilities may influence profitability and overall efficient with respect to customer needs, wants and preferences.

Type of Facility

The paper evaluates the use of modelling techniques as a means of analyzing and delivering on effective means of selection locations for facilities such as plants and distribution centers. The paper provides a general approach for logistical support centers that are critical for effective supply chains. In addition, the author also considers the problems associated with two-stage nature facility location challenges.

Modelling Approaches

Two primary forms of location modelling are provided within the text namely robust and stochastic objectives locations. They vary in terms of their respective levels of uncertainty and associated objectives used in selection of locations. They are namely stochastic and robust location problems. Stochastic location modelling refers to first stage decision-making and second stage as the assignment of customers, which is also referred to as a recourse decision. On the other hand, robust modelling is seen as modelling technique used when the uncertainty parameters are unknown such as costs anticipated and objectives of the location. It includes the use of minimax for both cost and regret in selection of a facility location. In addition, these variables can be seen as either continues or robust. Discrete parameters use a scenario approach for modelling whereas the continuous parameters apply predetermined intervals.

It is important to note that in the evaluation of facility locations under conditions of uncertainty, minimization of costs and regrets associated poor choice selection a variety of options or models can be used. Such models vary on the need and application and include:

  1. Algorithms for Solving Minimax Problems:

This is understood as the use of exact algorithms as a means of evaluates the problems associated with minimax objectives. It is important to note that there are limited algorithms that can be used on general problems and networks within distributions and more towards selection of facility locations. The available algorithms are only applicable to structured problems and possess limited abilities for direct applications.

  1. Multiechelon Models:

Multiechelon locations are a recent discovery by researchers towards facility selection. This is elative to supply chain networks or multiechelon locations with an aim of developing solutions towards problems under uncertainty in facility location selection. Varieties of challenges abound given the use of stochastic objectives as opposed to robust goals.

  • SP Technology

Optimization technology developed by SP professionals and researchers has been integral towards development of solutions for facility location selection and other logistical and distribution problems. SP technology is evolving which provides an opportunity for effective strategies that can be used to provide appropriate solutions for logistical and supply chain problems.

  1. Meta-Heuristics for General Problems

Meta-heuristics is a widely used approach, which has been successful in the determination of location selection problems. In addition, it also takes into account the stochastic and robust objectives. This modelling strategy is preferred because it provides for flexibility and alterations in regard to objective functions and the various constraints with a high level of ease.




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