CMieux: Adaptive strategies for competitive supply chain trading

Benisch, Michael; Sardinha, Alberto; Andrews, James R.; Ravichandran, Ramprasad; Sadeh, Norman

doi:10.1016/j.elerap.2008.09.005

Cited by 16 publications

(19 citation statements)

References 4 publications

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“…Bids on RFQs (if any) depend on the probabilities of these bids to be accepted, which TacTex predicts using linear regression and adapts to the behavior of opponents. CMieux [21] uses a similar, yet somewhat less complex approach. CMieux predicts demand as well as selling prices using a Poisson distribution.…”

Section: Regimes and Tac Scmmentioning

confidence: 98%

Towards a dynamic model of supply chain regimes for complex multi-agent markets

Hogenboom

Kaymak

et al. 2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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Information systems are crucial for effective supply chain management in today's complex supply chains for durable goods. Complex decision making processes on strategic, tactical, and operational level require substantial support in order to contribute to the agility of organizations. Supply chain regimes, i.e., regimes encompassing both the sales and the procurement market in a complex supply chain, provide a way of intuitively and meaningfully characterizing and modeling supply chain mar ket conditions without a need for explicit modeling of individual aspects of the market. This paper makes a first explorative step towards a model incorporating such regimes, while maintaining the dynamics which enable the model to be utilized in the sales process, e.g., for dynamic product pricing. Initial results show that supply chain regimes have feasible characteristics, based on both sales and procurement market indicators. Taking into consideration these regimes enables a more deliberate sales model.

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Section: Regimes and Tac Scmmentioning

confidence: 98%

Towards a dynamic model of supply chain regimes for complex multi-agent markets

Hogenboom

Kaymak

et al. 2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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“…The methods used by the teams include fuzzy reasoning inference mechanisms [27], additive regression with decision stumps [42], linear regression [3], linear cumulative density function (CDF) [5], reverse CDF [32], continuous knapsack problem [4], dynamic pricing [8,29], and k-nearest neighbors [13,34]. The comparison analysis of various predicting algorithms [43] demonstrates superior performance of machine learning algorithms over traditional statistical approaches.…”

Section: Related Workmentioning

confidence: 99%

Learning approaches for developing successful seller strategies in dynamic supply chain management

Fasli

Kovalchuk

2011

Information Sciences

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“…Acceptance probability distributions could also be trained off-line [2]. Another option is to try to model the decision function of the accepting entities, based on their decision histories, e.g., using Chebychev polynomials [29].…”

Section: Related Workmentioning

confidence: 99%

Product pricing using adaptive real-time probability of acceptance estimations based on economic regimes

Hogenboom

Ketter

Dalen

et al. 2009

Proceedings of the 11th International Conference on Electronic Commerce

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In today's complex supply chains, product pricing is a vital, yet non-trivial task. We propose a product pricing approach using adaptive real-time probability of acceptance estimations based on economic regimes. Radial Basis Function Networks are trained to estimate parameters for doublebounded log-logistic distributions assumed to be underlying daily offer prices, using information available real-time. The relation between data and parameters is dynamically modeled using economic regimes (characterizing market conditions) and error terms (accounting for customer feedback). Given the parametric approximations of price distributions, acceptance probabilities are estimated using a closed-form mathematical expression, which is used to determine the price yielding a desired quota. The approach is implemented in the MinneTAC agent and tested against a price-following product pricing method in the TAC SCM game. Performance significantly improves; more customer orders are obtained against higher prices and profits more than double.

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CMieux: Adaptive strategies for competitive supply chain trading

Cited by 16 publications

References 4 publications

Towards a dynamic model of supply chain regimes for complex multi-agent markets

Towards a dynamic model of supply chain regimes for complex multi-agent markets

Learning approaches for developing successful seller strategies in dynamic supply chain management

Product pricing using adaptive real-time probability of acceptance estimations based on economic regimes

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