A multi-unit combinatorial auction based approach for decentralized multi-project scheduling
In industry, many problems are considered as the decentralized resource-constrained multi-project scheduling problem (DRCMPSP). Existing approaches encounter difficulties in dealing with large DRCMPSP cases while respecting the information privacy requirements of the project agents. In this paper, w...
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sg-ntu-dr.10356-831242020-03-07T11:48:55Z A multi-unit combinatorial auction based approach for decentralized multi-project scheduling Song, Wen Kang, Donghun Zhang, Jie Xi, Hui School of Computer Science and Engineering Rolls-Royce@NTU Corporate Lab Engineering::Computer science and engineering Multi-project Scheduling Multi-unit Combinatorial Auction In industry, many problems are considered as the decentralized resource-constrained multi-project scheduling problem (DRCMPSP). Existing approaches encounter difficulties in dealing with large DRCMPSP cases while respecting the information privacy requirements of the project agents. In this paper, we tackle DRCMPSP by formulating it as a multi-unit combinatorial auction (Wellman et al. in Games Econ Behav 35(1):271–303, 2001), which does not require sensitive private project information. To handle the hardness of bidder valuation, we introduce the capacity query which uses different item capacity profiles to efficiently elicit valuation information from bidders. Based on the capacity query, we adopt two existing strategies (Gonen and Lehmann in Proceedings of the 2nd ACM conference on electronic commerce, pp 13–20, 2000) for solving multi-unit winner determination problems to find good allocations of the DRCMPSP auctions. The first strategy employs a greedy allocation process, which can rapidly find good allocations by allocating the bidder with the best answer after each query. The second strategy is based on a branch-and-bound process to improve the results of the first strategy, by searching for a better sequence of granting the bids from the bidders. Empirical results indicate that the two strategies can find good solutions with higher quality than state-of-the-art decentralized approaches, and scale well to large-scale problems with thousands of activities from tens of projects. NRF (Natl Research Foundation, S’pore) 2019-07-03T04:22:33Z 2019-12-06T15:12:16Z 2019-07-03T04:22:33Z 2019-12-06T15:12:16Z 2017 Journal Article Song, W., Kang, D., Zhang, J., & Xi, H. (2017). A multi-unit combinatorial auction based approach for decentralized multi-project scheduling. Autonomous Agents and Multi-Agent Systems, 31(6), 1548-1577. doi:10.1007/s10458-017-9370-z 1387-2532 https://hdl.handle.net/10356/83124 http://hdl.handle.net/10220/49103 10.1007/s10458-017-9370-z en Autonomous Agents and Multi-Agent Systems © 2017 The Author(s). All rights reserved. |
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Engineering::Computer science and engineering Multi-project Scheduling Multi-unit Combinatorial Auction Song, Wen Kang, Donghun Zhang, Jie Xi, Hui A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
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In industry, many problems are considered as the decentralized resource-constrained multi-project scheduling problem (DRCMPSP). Existing approaches encounter difficulties in dealing with large DRCMPSP cases while respecting the information privacy requirements of the project agents. In this paper, we tackle DRCMPSP by formulating it as a multi-unit combinatorial auction (Wellman et al. in Games Econ Behav 35(1):271–303, 2001), which does not require sensitive private project information. To handle the hardness of bidder valuation, we introduce the capacity query which uses different item capacity profiles to efficiently elicit valuation information from bidders. Based on the capacity query, we adopt two existing strategies (Gonen and Lehmann in Proceedings of the 2nd ACM conference on electronic commerce, pp 13–20, 2000) for solving multi-unit winner determination problems to find good allocations of the DRCMPSP auctions. The first strategy employs a greedy allocation process, which can rapidly find good allocations by allocating the bidder with the best answer after each query. The second strategy is based on a branch-and-bound process to improve the results of the first strategy, by searching for a better sequence of granting the bids from the bidders. Empirical results indicate that the two strategies can find good solutions with higher quality than state-of-the-art decentralized approaches, and scale well to large-scale problems with thousands of activities from tens of projects. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Song, Wen Kang, Donghun Zhang, Jie Xi, Hui |
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Article |
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Song, Wen Kang, Donghun Zhang, Jie Xi, Hui |
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Song, Wen |
title |
A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
title_short |
A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
title_full |
A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
title_fullStr |
A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
title_full_unstemmed |
A multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
title_sort |
multi-unit combinatorial auction based approach for decentralized multi-project scheduling |
publishDate |
2019 |
url |
https://hdl.handle.net/10356/83124 http://hdl.handle.net/10220/49103 |
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