An approach to solve winner determination in combinatorial reverse auctions using genetic algorithms

Shil, Shubhashis Kumar; Mouhoub, Malek; Sadaoui, Samira

doi:10.1145/2464576.2464611

Cited by 8 publications

(8 citation statements)

References 6 publications

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“…Combinatorial auctions provide a more efficient allocation than standard auctions in a multi-item scenario [1,2,4]. In [15,16], we have used GAs to solve the winner determination problem in the context of combinatorial reverse auctions. In our proposed GACRA method [15,16], infeasible chromosomes are repaired by removing redundancy and emptiness through two repairing methods.…”

Section: Genetic Algorithms In Combinatorial Reverse Auctionsmentioning

confidence: 99%

“…In [15,16], we have used GAs to solve the winner determination problem in the context of combinatorial reverse auctions. In our proposed GACRA method [15,16], infeasible chromosomes are repaired by removing redundancy and emptiness through two repairing methods. Emptiness means a chromosome in which some item(s) are not selected, while in redundancy some item(s) are chosen more than once.…”

Section: Genetic Algorithms In Combinatorial Reverse Auctionsmentioning

confidence: 99%

“…Nevertheless, not much work has been done by using GAs to solve the winner determination problem in the context of combinatorial reverse auctions. In [15,16], we have proposed a GA based method that we called GACRA (Genetic Algorithm for Combinatorial Reverse Auctions) to tackle this problem. GACRA is successful in finding optimal solutions; however, it needs comparatively a considerable amount of time to produce good solutions as it uses two repairing methods.…”

Section: Introductionmentioning

confidence: 99%

“…Our research goal here is twofold: 1) solve the winner determination problem in combinatorial reverse auctions in a reasonable processing time, and 2) reduce the procurement cost with fewer generations. For this purpose, we improve the method GACRA described in [15,16] and name our new method Improved Genetic Algorithms for Combinatorial Reverse Auctions (IGACRA). IGACRA only uses one repairing function to repair infeasible chromosomes.…”

Section: Introductionmentioning

confidence: 99%

“…The rest of the paper is organized as follows. In Section 2, the literature related to this research work is discussed with a focus on winner determination and genetic algorithms, and briefly outlines how GACRA is used in [15,16] to address the winner determination problem. In Section 3, the proposed IGACRA is presented in detail through an example.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Evolutionary Techniques for Reverse Auctions

Shil¹,

Sadaoui²,

Mouhoub³

2013

ICA

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Winner determination is one of the main challenges in combinatorial auctions. However, not much work has been done to solve this problem in the case of reverse auctions using evolutionary techniques. This has motivated us to propose an improvement of a genetic algorithm based method, we have previously proposed, to address two important issues in the context of combinatorial reverse auctions: determining the winner(s) in a reasonable processing time, and reducing the procurement cost. In order to evaluate the performance of our proposed method in practice, we conduct several experiments on combinatorial reverse auctions instances. The results we report in this paper clearly demonstrate the efficiency of our new method in terms of processing time and procurement cost.

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