期刊
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 272, 期 3, 页码 1158-1172出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2018.07.027
关键词
(R) OR in energy; Strategic bidding; MPEC; Robust optimization; Sealed-bid uniform-price auction
资金
- Ministry of Education of Brazil [6540/155]
- National Science Foundation [1633196]
- Office of Naval Research grant [N000141812075]
- CNPq [302092/2017-0]
- FAPERJ [E-26/203.285/2017]
- CAPES Foundation
- U.S. Department of Defense (DOD) [N000141812075] Funding Source: U.S. Department of Defense (DOD)
In this paper, we propose an alternative methodology for devising revenue-maximizing strategic bids under uncertainty in the competitors' bidding strategy. We focus on markets endowed with a sealed-bid uniform-price auction with multiple divisible products. On recognizing that the bids of competitors may deviate from equilibrium and are of difficult statistical characterization, we proposed a two-stage robust optimization model with equilibrium constraints aiming to devise risk-averse strategic bids. The proposed model is a trilevel optimization problem that can be recast as a particular instance of a bilevel program with equilibrium constraints. Reformulation procedures are proposed to find a single-level equivalent formulation suitable for column-and-constraint generation (CCG) algorithm. Results show that even for the case in which an imprecision of 1% is observed on the rivals' bids in the equilibrium point, the robust solution provides a significant risk reduction (of 79.9%) in out-of-sample tests. They also indicate that the best strategy against high levels of uncertainty on competitors' bid approaches to a price-taker offer, i.e., bid maximum capacity at marginal cost. (C) 2018 Elsevier B.V. All rights reserved.
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