Monday, November 17, 2008

AMHS Issue and a Proactive OR Approach

Moving materials in a complex manufacturing environment is a difficult task. If you consider an average of 600-step process route requiring material movement between every step, managing those vehicles sometimes could be more difficult than managing the value added production itself. In contrast to machines, material handling vehicles are not fixed, they move around. Modeling them as another regular resource is not an option in this case.

Actually, it is not always the modeling or algorithm problem. Many times, it may be the infrastructure, which is beyond an Operations Research analyst's view. In many cases, it is hard to track vehicles or provide sufficient communication capabilities between machines, jobs and vehicles.

However, showing that an optimization based solution could make the overall system work better than the best solution that can be found within current infrastructure forces the hardware suppliers to design their equipments with better communication or tracking capabilities. This scenario is one of the many more examples existing in the real world, in which an OR expert can take proactive steps to change the environment to a better condition to work on. An optimization model is not always supposed to formed within the given constraints, it can also create its own constraint set.

Monday, November 3, 2008

Taking advantage of the market crash

A crash in the financial market is not essentially bad for everyone. There are a number of industries that thrive in such an environment. For example, the repossessed vehicle market is overflowing with inventory. While this may hurt banks and other financial institutions that are willing to auction off these vehicles to cut their losses, there are many people out there who wouldn't mind driving a nicer car without having to pay the price, well, at least not the sticker price...

According to npr, "vehicle repossessions are up 10% this year" and approximately 1.6 million vehicles are estimated to be repossessed by the end of the year. As a result, some lending companies are starting to 'adjust' the loans with the borrowers instead of repossessing their vehicles.

From the lenders point of view, an interesting optimization problem would be to identify the optimal number of vehicles to repossess versus adjust. A number of lending companies might be interested in such a problem due to the complexity of this decision. The amount of money saved due to repossessing the vehicle should offset the opportunity cost of receiving payments from the buyer as well as the logistics and inventory cost of transporting and holding repossessed vehicles. Such an optimization problem would also incorporate a 'risk' factor that includes the probability that borrowers may in fact pull themselves out of the economic trough sooner than later.

Food for thought...

Where does academy and industry differ?

Both academy and industry aim to produce work for the good of humanity. Although underlying personal aims could be different, such as greed to publish papers, higher profits, etc., they all satisfy in some demand due to human beings' needs or questions.

The methods that are used by both theoretical and practical sides support themselves, they all root back to scientific method. While academic production has very detailed reviewing steps, it is easier to assess the output of an industrial work. While many less credited academic works show great benefits in the industry, many academic milestone works cannot find a chance of direct implementation into practice.

Both industry and academy need themselves to survive. There would not be any problems to solve if there was not industry or industry would fail due to myopic solutions if there was not more global insight of the academy.

But where does an academic work differ from an industrial work? Even enabling a very highly complex system to work with little flaws needs a lot of intellectual work in itself. Everyday practice translates into improvement in many cases. However, this may not be considered as credible academically. Academy needs a new problem to be defined, or a new method to be developed to solve an existing problem or a better method than existing solution methods to solve an existing problem. Someone other than the researcher gives the final decision how academically credible the work the researcher has done. There are not always objective evaluation methods as opposed to evaluation methods that industry has. While an expert can consider a work substantially contributory, another cannot see any contribution. It is a hard job for both the researcher and the referee to decide on the quality of a paper.