Evolution of a supply chain management game for the trading agent competition

TAC SCM is a supply chain management game for the Trading Agent Competition (TAC). The purpose of TAC is to spur high quality research into realistic trading agent problems. We discuss TAC and TAC SCM: game and competition design, scientific impact, and lessons learnt

Flexible Decision Control in an Autonomous Trading Agent

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM).autonomous trading agent;decision processes

Detecting and Forecasting Economic Regimes in Multi-Agent Automated Exchanges

We show how an autonomous agent can use observable market conditions to characterize the microeconomic situation of the market and predict future market trends. The agent can use this information to make both tactical decisions, such as pricing, and strategic decisions, such as product mix and production planning. We develop methods to learn dominant market conditions, such as over-supply or scarcity, from historical data using Gaussian mixture models to construct price density functions. We discuss how this model can be combined with real-time observable information to identify the current dominant market condition and to forecast market changes over a planning horizon. We forecast market changes via both a Markov correction-prediction process and an exponential smoother. Empirical analysis shows that the exponential smoother yields more accurate predictions for the current and the next day (supporting tactical decisions), while the Markov correction-prediction process is better for longer term predictions (supporting strategic decisions). Our approach offers more flexibility than traditional regression based approaches, since it does not assume a fixed functional relationship between dependent and independent variables. We validate our methods by presenting experimental results in a case study, the Trading Agent Competition for Supply Chain Management.dynamic pricing;machine learning;market forecasting;Trading agents

Real-time Tactical and Strategic Sales Management for Intelligent Agents Guided By Economic Regimes

Many enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real-time. We describe a family of statistical models that address these needs by combining characterization of the economic environment with the ability to predict future economic conditions to make tactical (short-term) decisions, such as product pricing, and strategic (long-term) decisions, such as level of finished goods inventories. Our models characterize economic conditions, called economic regimes, in the form of recurrent statistical patterns that have clear qualitative interpretations. We show how these models can be used to predict prices, price trends, and the probability of receiving a customer order at a given price. These “regime†models are developed using statistical analysis of historical data, and are used in real-time to characterize observed market conditions and predict the evolution of market conditions over multiple time scales. We evaluate our models using a testbed derived from the Trading Agent Competition for Supply Chain Management (TAC SCM), a supply chain environment characterized by competitive procurement and sales markets, and dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and longterm resource allocation decisions. Results show that our method outperforms more traditional shortand long-term predictive modeling approaches.dynamic pricing;trading agent competition;agent-mediated electronic commerce;dynamic markets;economic regimes;enabling technologies;price forecasting;supply-chain

A demand-driven approach for a multi-agent system in Supply Chain Management

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit. © 2010 Springer-Verlag Berlin Heidelberg

An Investigation Report on Auction Mechanism Design

Auctions are markets with strict regulations governing the information available to traders in the market and the possible actions they can take. Since well designed auctions achieve desirable economic outcomes, they have been widely used in solving real-world optimization problems, and in structuring stock or futures exchanges. Auctions also provide a very valuable testing-ground for economic theory, and they play an important role in computer-based control systems. Auction mechanism design aims to manipulate the rules of an auction in order to achieve specific goals. Economists traditionally use mathematical methods, mainly game theory, to analyze auctions and design new auction forms. However, due to the high complexity of auctions, the mathematical models are typically simplified to obtain results, and this makes it difficult to apply results derived from such models to market environments in the real world. As a result, researchers are turning to empirical approaches. This report aims to survey the theoretical and empirical approaches to designing auction mechanisms and trading strategies with more weights on empirical ones, and build the foundation for further research in the field

Regional monopoly and interregional and intraregional competition: the parallel trade in Coca-Cola between Shanghai and Hangzhou in China

This article uses a “principal-agent-subagent” analytical framework and data that were collected from field surveys in China to (1) investigate the nature and causes of the parallel trade in Coca-Cola between Shanghai and Hangzhou and (2) assess the geographic and theoretical implications for the regional monopolies that have been artificially created by Coca-Cola in China. The parallel trade in Coca-Cola is sustained by its intraregional rivalry with Pepsi-Cola in Shanghai, where Coca-Cola (China) (the principal) seeks to maximize its share of the Shanghai soft-drinks market. This goal effectively supersedes the market-division strategy of Coca-Cola (China), since the gap in wholesale prices between the Shanghai and Hangzhou markets is higher than the transaction costs of engaging in parallel trade. The exclusive distributor of Coca-Cola in the Shanghai market (the subagent) makes opportunistic use of a situation in which it does not have to bear the financial consequences of the major residual claimants (the principal and other agents) and has an incentive to enter the nondesignated Coca-Cola market of Hangzhou by crossing the geographic boundary between the two regional monopolies devised by Coca-Cola. The existence of parallel trade in Coca-Cola promotes interregional competition between the Shanghai and Hangzhou bottlers (the agents). This article enhances an understanding of the economic geography of spatial equilibrium, disequilibrium, and quasi-equilibrium of a transnational corporation's distribution system and its artificially created market boundary in China

While Doha Sleeps: Securing Economic Growth through Trade Facilitation

Improving the international trading system does not require new, comprehensive multilateral agreements. Countries can derive large gains from the trading system by engaging in reforms often referred to as trade facilitation. In broad terms, trade facilitation includes reforms aimed at improving the chain of administrative and physical procedures involved in the transport of goods and services across international borders. Countries with inadequate trade infrastructure, burdensome administrative processes, or limited competition in trade logistics services are less capable of benefiting from the opportunities of expanding global trade. Companies interested in investing, buying, or selling in local markets are less likely to bother if there are too many frictions related to document processing or cargo inspection at customs, antiquated port facilities, logistics bottlenecks, or limited reliability of freight or trade-financing services. According to recent studies from the World Bank and other international economic institutions, trade facilitation reforms could do more to increase global trade flows than further reductions in tariff rates. For many developing countries -- particularly those that receive preferential tariff treatment from rich countries -- reducing transportation and logistics-related costs through trade facilitation reforms would be much more beneficial than further tariff cuts. But trade facilitation does not only offer promise to developing countries. All countries can benefit by removing sources of friction in their supply chains. The post-9/11 focus on minimizing the risk of terrorists exploiting porous international supply chains to sneak weapons of mass destruction into U.S. cities -- obviously a vital objective -- could hamper the capacity of Americanbased companies to attract investment and compete for markets. Likewise, U.S. prohibitions against foreign competition in transportation services and the political antipathy toward foreign investment in U.S. port operations raise the costs of doing business and increase the scope for trade facilitation in the United States