Supply Chain Management: Market-Share

Matthew J. OlsonCIS 690 Research ProjectDr. Hsu

Introduction Background: What is TAC-SCM The Base Agent: MinneTAC Why I Studied Market-Share Methodology: Winter’s Method Experiment Results Agent Variations The Second Experiment Results Conclusions

Background The Trading Agent Competition – Supply Chain

Management (TAC-SCM) Each game has 6 autonomous agents buying

computer parts, building computers, and selling them to customers.

A game is 220 days in length. Each agent starts with a $0 balance and can

take loans. Interest on loans are charged. Interest on positive balance is given. A cost is associated with storage. The winner is the one with the biggest bank

balance at the end of the game.

Background (cont.)

Background (cont.)

Background (cont.)

MinneTAC

Minnesota’s TAC-SCM agent Code was given under the open source

license. After coming in 25th in the 2004

competition, they made some improvements and released this version.

One documented short-coming was market-share.

Why I Studied Market-Share

Market-share was assumed at 1/6. (MinneTAC was one of six agents playing in a game.)

In the real world, market-share isn’t so quaint.

In the game, it isn’t a bad starting estimate, but as time goes on…

MinneKatTAC

Methodology: Winter’s Method

Level: Ei=U(Ei-1+Ti-1)+(1-U)Yi

Trend: Ti=VTi-1+(1-V)(Ei-Ei-1)

U & V derived from experimentation. Y is the observed value (in our case,

(our orders)/(total orders) )

Methodology: Winter’s Method (cont.)

double marketShare=1.0/6.0;double marketShareOld;double level=1.0/6.0;double levelOld;double u=0.995;double v=0.995;double minMarketShare=0.05;double maxMarketShare=0.5;

CustomerOrderList orderList = repository.getCustomerOrders();

for(int i=0;i<catalog.size();i++){ totalOrders+=

repository.getProductsOrdered(i);}

ourOrders=(double)orderList.size();if(totalOrders>0.0) { double orderRatio=ourOrders/totalOrders; marketShareOld=marketShare; levelOld=level; level=u*(levelOld+marketShareOld)+(1-

u)*orderRatio; marketShare=v*marketShareOld+(1-v)*(level-

levelOld); if(marketShare<minMarketShare) marketShare=minMarketShare; if(marketShare>maxMarketShare) marketShare=maxMarketShare;}

Experiment Results 68.2%Game Results

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Experiment Results 68.2%Average Revenue

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Agent Variations

Ran 5 versions and the baseline 0 – previously described 1 – averaged market-share over 2 days 2 – averaged market-share over 3 days 3 – averaged market-share over 4 days 4 – halved market-share for 1st 22 days

The Second Experiment ResultsGame Results

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The Second Experiment ResultsGame Results

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Conclusions

The modified agent is beating the baseline a majority of the time!

This shows that market-share is an important factor.

I would stand behind this agent in a competition!

References

Berenson, Mark L., et al. Basic Business Statistics: Concepts and Apllications. Tenth Ed. 679.

Collins, John, et al. The Supply Chain Management Game for the 2006 Trading Agent Competition. November 2005. <http://www.sics.se/tac/tac06scmspec_v16.pdf>.

Collins, John, et al. MinnieTAC. University of Minnesota. <http://www.cs.umn.edu/tac/source.html>.

Collins, John, et al. Component-based Design for a Trading Agent. July 2004. <http://www.cs.umn.edu/tac/release/minnetac_design.pdf>.

Questions

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