An Equilibrium-Based Approach for Determining Winners in Combinatorial Auctions

Tsung, Chen-Kun; Ho, Hann‐Jang; Lee, SingLing

doi:10.1109/ispa.2011.13

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…NESA is able to produce near to optimal solutions. Moreover [6] showed that NESA performs pretty well for large (2000 bidders and 200 items) and small (1000 bidders and 100 items) scale settings. They also discussed the stability of Nash Equilibrium to solve the WD problem in combinatorial auctions.…”

Section: Evolutionary Wd Techniquesmentioning

confidence: 99%

“…Auctions can be technology specific (one or more renewable energy) or neutral (past and new technology) [5]. Renewable energy, especially wind and solar, has performed successfully in the markets, and its usage is increasing rapidly due to the environmental concerns [6]. For instance, renewable energy grew by 66.4% in 2012 in the Brazilian market [7], and by 60% in 2013 in the Spanish market [3].…”

Section: Scope and Problemmentioning

confidence: 99%

“…Reference [21] claimed that when the resource allocation problem has feasible solutions, then Nash equilibrium is always guaranteed. Moreover, in [6], the authors proposed a Nash Equilibrium Search Approach (NESA) that consists of a local search procedure and an evolutionary algorithm. They solved the WD problem in the context of standard combinatorial auctions, and validated the WD procedure by measuring the performance of their Nash-Equilibrium solution based on revenue performance, anytime performance and optimal solution comparison.…”

Section: Evolutionary Wd Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

Meeting peak electricity demand through combinatorial reverse auctioning of renewable energy

Shil

Sadaoui

2017

J. Mod. Power Syst. Clean Energy

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The option of organizing E-auctions to purchase electricity required for anticipated peak load period is a new one for utility companies. To meet the extra demand load, we develop electricity combinatorial reverse auction (CRA) for the purpose of procuring power from diverse energy sources. In this new, smart electricity market, suppliers of different scales can participate, and homeowners may even take an active role. In our CRA, an item, which is subject to several trading constraints, denotes a time slot that has two conflicting attributes, electricity quantity and price. To secure electricity, we design our auction with two bidding rounds: round one is exclusively for variable energy, and round two allows storage and nonintermittent renewable energy to bid on the remaining items. Our electricity auction leads to a complex winner determination (WD) task that we represent as a resource procurement optimization problem. We solve this problem using multi-objective genetic algorithms in order to find the trade-off solution that best lowers the price and increases the quantity. This solution consists of multiple winning suppliers, their prices, quantities and schedules. We validate our WD approach based on large-scale simulated datasets. We first assess the time-efficiency of our WD method, and we then compare it to well-known heuristic and exact WD techniques. In order to gain an exact idea about the accuracy of WD, we implement two famous exact algorithms for our constrained combinatorial procurement problem.

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Section: Evolutionary Wd Techniquesmentioning

confidence: 99%

Section: Scope and Problemmentioning

confidence: 99%

Section: Evolutionary Wd Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Meeting peak electricity demand through combinatorial reverse auctioning of renewable energy

Shil

Sadaoui

2017

J. Mod. Power Syst. Clean Energy

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“…The second group of studies solves the problem to optimality using various branching methods (Fujishima et al., 1999; Sandholm et al., 2005). The third group of studies develops heuristics approaches, which include virtual simultaneous auctions (Fujishima et al., 1999), equilibrium heuristics (Tsung et al., 2011), and tabu search heuristics (Wu and Hao, 2015).…”

Section: Introductionmentioning

confidence: 99%

Solving the winner determination problem in combinatorial auctions for fractional ownership of autonomous vehicles

Takalloo

Bogyrbayeva

Charkhgard

et al. 2020

Int Trans Operational Res

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The introduction of autonomous vehicles (AVs) to consumer markets will expedite the trend of car sharing and enable co‐owning or co‐leasing a car. In this paper, we consider a combinatorial auction market for fractional ownership of AVs, which is unique in two aspects. First, items are neither predefined nor discrete; rather, items are continuous time slots defined by bidders. Second, the spatial information of bidders should be incorporated within the winner determination problem (WDP) so that sharing a vehicle is indeed a viable plan. The consideration of spatial information increases the computational complexity significantly. We formulate the WDP, which plays a critical role in various auction designs and pricing schemes, for both discrete‐ and continuous‐time settings. In terms of social welfare maximization, we show that the continuous‐time model is superior to the discrete‐time model. We provide a conflict‐based reformulation of the continuous‐time model, for which we develop an effective solution approach based on a heuristic and maximal clique based reformulations. Using samples of the 2010–2012 California Household Travel Survey, we verify that the proposed solution methods provide effective computational tools for the combinatorial auction with bidder‐defined items.

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Solving the winner determination problem via a weighted maximum clique heuristic

Hao

2015

Expert Systems with Applications

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An Equilibrium-Based Approach for Determining Winners in Combinatorial Auctions

Cited by 4 publications

References 5 publications

Meeting peak electricity demand through combinatorial reverse auctioning of renewable energy

Meeting peak electricity demand through combinatorial reverse auctioning of renewable energy

Solving the winner determination problem in combinatorial auctions for fractional ownership of autonomous vehicles

Solving the winner determination problem via a weighted maximum clique heuristic

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