Negotiation-Based Capacity Planning With A Learning Mechanism Using Adaptive Neurofuzzy Inference System

Fikri, Aulia Rahman Mufti (2016) Negotiation-Based Capacity Planning With A Learning Mechanism Using Adaptive Neurofuzzy Inference System. Masters thesis, Institut Technology Sepuluh Nopember.

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Abstract

In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufacturing resources that are scattered over individual factories. The outcome of the experiments shows good prediction of the opponent offers during negotiation, so it enables the reduction of negotiation time.

Item Type: Thesis (Masters)
Additional Information: RTI 629.831 2 Fik n
Uncontrolled Keywords: Automated negotiation, capacity planning, learning mechanism, negotiation decision function
Subjects: Q Science > QA Mathematics > QA9.64 Fuzzy logic
Divisions: Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis
Depositing User: Mr. Tondo Indra Nyata
Date Deposited: 17 Feb 2020 06:30
Last Modified: 17 Feb 2020 06:30
URI: http://repository.its.ac.id/id/eprint/74980

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