Compare and Contrast the Factor-Rating System and the Transportation Method of Linear Programming

Compare and contrast the factor-rating system and the transportation method of linear programming as used in facility location decisions. Which method employs substantially more mathematical rigor? What limitations can this bring to the analysis technique? What are some of the issues associated with making a facility decision from a large number of candidate locations? Identify the strengths and weaknesses of each method. How can these methods be blended to achieve the strengths and lessen the problems of each? Reference newsworthy facility location decisions that you are aware of, and suggest what types of factors were considered in the decision.

Both labor and customers must be considered in facility location decisions. In addition, suppliers, business climate, and competition must also be considered. And, while it is prudent to contemplate these strategic points, it is also wise to factor in risks such as political, environmental and trade.

Because they are easy to understand and "provide a mechanism to combine diverse factors", (e.g., labor climate, living conditions, transportation, water supply, tax policies and laws), factor rating systems are commonly used to determine facility location decisions. That said, "they do not account for the wide range of costs that may occur within each factor" (Bartness, A. , 1994). For this reason, factor rating systems, unless utilizing a weighted averaging system that attempts to accurately account for real costs, may generate results that are misleading.

In contrast, the transportation method (also known as the linear programming method) utilizes a matrix to, "minimize the cost of shipping n units to m destinations or", "maximize the profit of shipping n units to m destinations" (Jacobs and Chase, 2011). Because this method only considers facility location from a shipping expense/profit position, it can miss the real cost of operating a business that must deal with tariffs, political landscape, competitive forces, the local labor market and the local business climate. Another limitation to the linear programming method is addressing 'soft problems' such as subjective judgements and preferences, risk tolerances and trade-offs . These features are not appropriate for hard-problem resolution" according to Jeanne Cochran. (Cochran, J., 2004) A third limitation as discussed at rincondelvago is, "Therefore this is another disadvantage of linear programming; graphical method can be used only under determined conditions. There may be another two problems consisting of numerous optimal solutions, this is not a simple matter despite the fact could seem a minor concern, and the other problem could be infeasibility. When no solution to the linear programming problem satisfies all the constraints, feasible region does not exist and therefore any solution cannot be reached." (Rincondelvago, 2010).

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