Manufacturing control with a market-driven contract net
Manufacturing control with a market-driven contract net
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Integer Programming for Combinatorial Auction Winner Determination
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Combinatorial Auctions: A Survey
INFORMS Journal on Computing
Product platform design and customization: Status and promise
Artificial Intelligence for Engineering Design, Analysis and Manufacturing - SPECIAL ISSUE: Platform product development for mass customization
Models for Iterative Multiattribute Procurement Auctions
Management Science
Taming the computational complexity of combinatorial auctions: optimal and approximate approaches
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Constraint-based winner determination for auction-based scheduling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An interactive service customization model
Information and Software Technology
Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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In mass customization, companies strive to enhance customer value by providing products and services that are approximate to customers' needs. A company's strategy of allocating its limited capacity to meeting diverse customer requirements directly impact customer perceived value in terms of available options, cost, and schedule. Proposed in this paper is an auction-based mass customization model for solving the problem of service customization under capacity constraints. The proposed model integrates customers' customization decision making with the allocation of company's capacity through multilateral negotiation between the company and its customers. The negotiation is conducted through a combinatorial iterative auction designed to maximize the overall customer value given limited capacity. The auction is incentive-compatible in the sense that customers will follow the prescribed myopic best-response bidding strategy. Experimental results indicate that customization solutions computed by the proposed model are very close to the optimal one. Revenue performance is also adequate when there is sufficient competition in the market.