PHYSICS APPLICATION ON LOGISTICS FOR BERTH ALLOCATION IN TPK KOJA, TANJUNG PRIOK PORT USING SIMULATED ANNEALING ALGORITHM
Complex systems exhibit emergent properties and behaviors that cannot be explained solely by the properties of their individual components, and they are studied in various fields such as physics, biology, and transportation. In the context of transportation and logistics, the complex systems appr...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/83267 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Complex systems exhibit emergent properties and behaviors that cannot be
explained solely by the properties of their individual components, and they are
studied in various fields such as physics, biology, and transportation. In the context
of transportation and logistics, the complex systems approach involves
characteristics like self-organization, stability, non-linearity, and adaptability.
Problems in transportation and logistics systems, especially in Indonesian ports, can
be analyzed through this approach. Tanjung Priok Port, as the largest and most vital
in Indonesia, plays a crucial role in the country's economy with its modern facilities
and integrated logistics system. Challenges arise when storms around Indonesia
seas disrupt berthing windows, forcing ships to dock simultaneously and disrupting
berth allocation according to the berthing contract, creating a dynamic berth
allocation problem (DBAP). Berth allocation must be dynamically adjusted, and
physics-based approaches like simulated annealing can be used to optimize berth
allocation. This final project consists of two phases: method testing and real data
testing. Method testing showed that 8 out of 10 problems achieved accurate
objective values for non-local optimal solutions, indicating that the simulated
annealing algorithm and berth allocation schedule sorting logic can be used for
more efficient berth allocation in busy ports. Real data testing demonstrated that
berth allocation using simulated annealing had a lower total cost (m) compared to
heuristic methods without optimization, namely 26225 compared to 30115. This
proves that the simulated annealing algorithm is effective in solving the berth
allocation problem (BAP).
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