An Optimized Multi-item Bilateral Negotiation Model

Mittal, Mandeep; Gaba, Divyansh; Rana, Hemant; Swain, Prabodh Ranjan

doi:10.1109/aicai.2019.8701240

Cited by 2 publications

(1 citation statement)

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“…Park and Yang proposed a multilateral efficient negotiation system 3 in pervasive computing environment, and used sorting method to match, achieving good results. Mandeep Mittal et al proposed a bilateral optimized model for negotiation between buyer and seller through a mediator agent to negotiate on the issue price and the quantity for multi-item 4 . Domestically, Shangwen Xing studied e-commerce automatic negotiation by using Agent negotiation theory and game theory 5 .…”

Section: Introductionmentioning

confidence: 99%

A multilateral fair negotiation model solved by Hungarian solution

Liu¹,

Song²,

Li³

et al. 2022

International Conference on Computer Application and Information Security (ICCAIS 2021)

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Multi-agent was introduced to study the issue of multilateral and multi-attribute fair negotiation in e-commerce. In this paper, a mathematical model is established through the Hungarian solution to solve the problem. Taking into account the multi-attribute and multilateral conditions and fairness in the negotiation, the real negotiation information is simulated in the form of randomly generated data, and the evaluation profit system and bilateral negotiation model are established to solve the problem and then the profit matrix can be obtained. Analogy 0-1 assignment problem is solved by Hungarian solution. Through numerical experiments and analysis, it indicates that this algorithm can obtain the overall maximum profit value that the system can achieve, and make the number of matching people as large as possible to achieve better negotiation results.

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Section: Introductionmentioning

confidence: 99%