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Design of Intelligent Agents for Supply Chain Management

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E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life (WEB 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 258))

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Abstract

Using intelligent agents can be a good alternative for the automated supply chain management in e-commerce environment and decision support in current commerce practices [8]. This study focuses on finding the optimal structure of intelligent agents that yield the best performance for supply chain management. This study was conducted in two phases. In the first phase, a model for agent was developed and implemented. In the model we applied Q-learning, Softmax function, and ε-greedy to control the inventory threshold dynamically and used a sliding window protocol for flexible bidding strategy. Also, a testing environment with competing agents was implemented. In the second phase, two agents of different types were tested against each other in the same simulation. This simulation was played twice to compare our agent with two other types of agents. Results of simulations shows that our agent has better performance in two different simulations.

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Authors and Affiliations

  1. Department of Information Systems, College of Business, University of Texas at Arlington, P.O. Box 19437, Arlington, TX, 76019, USA

    YoonSang Lee & Riyaz Sikora

Authors
  1. YoonSang Lee
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  2. Riyaz Sikora
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Correspondence to Riyaz Sikora .

Editor information

Editors and Affiliations

  1. Department of Decision and Information Sciences, Oakland University, Rochester, Michigan, USA

    Vijayan Sugumaran

  2. Virginia Commonwealth University, Richmond, Virginia, USA

    Victoria Yoon

  3. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA

    Michael J. Shaw

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Lee, Y., Sikora, R. (2016). Design of Intelligent Agents for Supply Chain Management. In: Sugumaran, V., Yoon, V., Shaw, M. (eds) E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life. WEB 2015. Lecture Notes in Business Information Processing, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-319-45408-5_3

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