E0 239 : Electronic commerce
Y. Narahari
e-Enterprises Laboratory
Department of Computer Science and Automation
Indian Institute of Science
Bangalore - 560 012
INDIA

VIPANI RELEASE 2


  1. Multi-Unit Single Item Reverse Auctions: Approximately- Strategyproof and Tractable Multi-Unit Auctions by Anshul Kothari, David C. Parkes, and Subhash Suri. In Decision Support Systems 39, 2005, pages 105-121 (Special issue dedicated to the Fourth ACM Conference on Electronic Commerce).
    The above paper presents an FPTAS for reverse auctions which you should implement. This has been covered in the class.

  2. Multi-Unit Single Item Forward Auctions: Approximately- Strategyproof and Tractable Multi-Unit Auctions by Anshul Kothari, David C. Parkes, and Subhash Suri. In Decision Support Systems 39, 2005, pages 105-121 (Special issue dedicated to the Fourth ACM Conference on Electronic Commerce).
    The above paper presents an FPTAS for reverse auctions. You should develop an FPTAS for forward auctions based on this and implement the same.

  3. Multi-Unit Procurement Auctions with Volume Discount Bids: Combinatorial and Quantity Discount Procurement Auctions Benefit Mars Incorporated and its Suppliers. by G. Hohner et al., Interfaces, Volume 33, Number 1, 2003.
    You should implement the formulation for volume discount procurement auctions with business constraints. This has been covered in the class.

  4. Multi-Unit Auctions modeled as a Nonconvex Knapsack Problem: S. Kameshwaran and Y. Narahari. Efficient Algorithms for Nonconvex Piecewise Linear Knapsack Problems. Working Paper, ECL-CSA Technical Report, Department of Computer Science and Automation, Indian Institute of Science, 2006.
    This paper develops several algorithms. You are required to implement the following: (a) Algorithm based on convex envelopes (b) 2-approximation algorithm (c) FPTAS.

  5. Branch and Bound Algorithm for Solving a Volume Discount Auction: S. Kameshwaran and Y. Narahari. A High Performance Branch and Bound Algorithm for Solving Piecewise Linear Knapsack Problems. ECL-CSA Technical Report, Department of Computer Science and Automation, Indian Institute of Science, 2006.
    This paper proposes a branch and bound algorithm for solving the winner determination problem of a volume discount auction. You are required to implement this algorithm.

  6. Discount Auctions for Combinatorial Procurement: S. Kameshwaran, L. Benyousef, and Xiaolan Xie. Discount Auctions for Procuring Heterogeneous Items. INRIA Research Report No. 6084, December 2006.
    This proposes two algorithms: BOS (Branch on Supply) and BOP (Branch on Price) for solving the winner determination problem in volume discount auctions arising in combinatorial procurement.

  7. Optimal Winner Determination in Combinatorial Auctions: Sandholm, T. 2002. Algorithm for Optimal Winner Determination in Combinatorial Auctions. Artificial Intelligence, 135, 1-54
    This proposes an efficient tree based algorithm for winner determination which you are required to implement.

  8. Multi-Unit Combinatorial Auctions: K. Leyton-Brown and Y. Shoham and M. Tennenboltz, An algorithm for multi-unit combinatorial auctions, Proceedings of National Conference on Artificial Intelligence, 2000 Paper-1 and Paper-2
    This proposes an algorithm for optimal winner determination in multi-unit multi-item auctions.

  9. Sponsored Search Auctions on the Web: Dinesh Garg, Y. Narahari, and Siva Sankar Reddy. Design of an Optimal Mechanism for Sponsored Searrch Auctions. ECL-CSA Technical Report, October 2006.
    This proposes an optimal mechanism for keyword auctions on the web. You are required to implement three mechanisms: GSP, VCG, and OPT and compare their performance.

  10. Multi-Attribute Exchange: G. Tewari and P. Maes. Design and implementation of an agent-based intermediary infrastructure for electronic markets, Proceedings of ACM Conference on Electronic Commerce, EC-2000, Minneapolis, Minnesota, USA, October 2000.
    This proposes a novel graph matching based algorithm for multi-attribute double auctions.

  11. Iterative Combinatorial Exchange: David C. Parkes, Ruggiero Cavallo, Nick Elprin, Adam Juda, Sebastien Lahaie, Benjamin Lubin, Loizos Michael, Jeffrey Shneidman, and Hassan Sultan. ICE: An Iterative Combinatorial Exchange In the Proc. 6th ACM Conf. on Electronic Commerce (EC'05), 2005
    You are required to implement an iterative combinatorial exchange here.

some important links:

 Modified by: NR Suri