The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICS AND COMPUTERS IN SIMULATION
Transactions ID Number: 20-843
Full Name: Anon Sukstrienwong
Position: Assistant Professor
Age: ON
Sex: Male
Address: Bangkok University, 40/4 Rama 4 Rd., Kloung-Toey, Bangkok, 10110
Country: THAILAND
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E-mail address: anon.su@bu.ac.th
Other E-mails: anon.su@yahoo.com
Title of the Paper: searching optimal buyer coalition structure by ant colony optimization
Authors as they appear in the Paper: Anon Sukstrienwong
Email addresses of all the authors: anon.su@bu.ac.th
Number of paper pages: 9
Abstract: In recent years, several buyer coalition schemes have been proposed by researchers in order to form effective coalitions and achieve the maximum benefit for consumers in an electronic market. However, there are few algorithms applying the ant colony optimization for forming buyer coalition. In this paper, we present the approach based on the Ant Colony Optimization (ACO). The approach called the Ant Colony Optimization for Forming of Buyer Coalition (ACO_FBC) algorithm for the formation of buyer coalition with bundles of items. The algorithm involves searching for the optimal buyer coalition structure by partitioning the whole group of buyers into smaller coalitions so that the aggregate of discount of the whole buyers is maximized. A number of artificial ants search to find the best disjoint subgroups of all buyers based on the total utility functions. The results of the ACO_FBC simulation are compared with the genetic algorithm (GAs) in the terms of the global op!
timal buyers' benefits. It indicates that in most situations our proposed algorithm significantly improves the utility of the buyer coalition.
Keywords: Ant colony optimization, Buyer coalition, Coalition structure, Electronic commerce, Simulation.
EXTENSION of the file: .doc
Special (Invited) Session: Forming Buyer Coalition with Bundles of Items by Ant Colony Optimization
Organizer of the Session: 510-187
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