PENGEMBANGAN MODEL INTEGRASI PENJADWALAN DAN PENGADAAN DENGAN MEMPERTIMBANGKAN PROSES NEGOSIASI MENGGUNAKAN ALGORITMA OPTIMASI INTERAKTIF MULTI-OBJEKTIF
The Indonesian fashion industry has a significant contribution towards the economy of the country, with a total revenue of up to US$ 13.323 trillion in 2021. However, the complexity of the industry requires collaboration and cooperation among stakeholders in the supply chain. One of the solutions...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/71054 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | The Indonesian fashion industry has a significant contribution towards the
economy of the country, with a total revenue of up to US$ 13.323 trillion in 2021.
However, the complexity of the industry requires collaboration and cooperation
among stakeholders in the supply chain. One of the solutions for this problem is
the fourth-party logistics (4PL) service providers, companies which provide
integrated supply chain management for industries. PT. A is a 4PL company
that provides services for local fashion MSMEs (Micro, Small, and Medium
Enterprises) in Indonesia. Recently, there were problems regarding the order
completion delay by up to 75% longer from its due date in one of its clients, PT.
X. The tardiness phenomenon is caused by production scheduling and the delay
in material arrivals from suppliers. Hence, integration between production
scheduling, material order schedule, as well as reliable suppliers will be needed
to fulfil the quantity, quality, and delivery due date requirements. Suppliers'
preference for material delivery might differ from the clients' preferred
production schedule. Hence, a mechanism to bridge this difference will also be
needed. To solve this problem, a multi-objective optimization model that
integrates production scheduling, material arrival planning, as well as supplier
selection is constructed. Then, Interactive Weighted Tchebycheff (IWT)
algorithm coupled with the forward filtering algorithm is deployed to solve the
model. The algorithm is designed to generate multiple solutions as an
alternative to the decision maker, so that strategic as well as subjective factors
which are hard to be mathematically modeled can be considered. Based on the
solution generation and negotiation simulation scenario, the model can slash
order completion time by around 43%-56% compared to the existing policy, and
also allow the incorporation of preferences of each stakeholder involved in the
negotiation. The negotiation algorithm can reach the local optimum status
under 1 hour of computation time.
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