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자료유형
학술저널
저자정보
저널정보
장전수학회 Advanced Studies in Contemporary Mathematics Advanced Studies in Contemporary Mathematics Vol.29 No.1
발행연도
2019.1
수록면
125 - 146 (22page)

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In this paper, we present a hybrid method for solving the multiitem multi-unit Winner Determination Problem of Combinatorial Auctions in the multi-attribute (multi-objective) context. Indeed, the bids may concern several speci cations of the item, involving not only its price, but also its quality, the delivery conditions, the delivery deadlines, the risk of not being paid after a bid has been accepted and so on. The problem is intractable and is equivalent to a Multi-Objective Multi-Constraint Knapsack Problem, a well known NP-Hard Problem. We propose a hybrid method, based on the Multi-Objective Branchand- Bound approach and the Random Walk Tabu Search metaheuristic. The Multi-Objective Branch-and-Bound used here is referred to be the process of the principal research. We present a novel rule to automatically rank bids while taking into account the Decision Makers's (DM's) preferences on objectives that are most relevant. A fuzzy dominance relation, on the discrete set of weight vectors, is then computed and used to rank bids and select a feasible solution (a subset of accepted bids). Numerical experiments are reported on data sets available in the literature, in the case of three objective functions, three items and the number of bids varying from 10 to 50. The obtained results show the e ciency of our Extended Multi-Objective Branch-and-Bound method that outperforms the existing Multi-Objective Branch-and-Bound methods both in terms of CPU time and ratio of dominated partial solutions. Furthermore, the hybrid method generates a larger number of e cient bids in reasonable time for all instances.

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