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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Bibliographic Details
Main Author: Putri Anggadinata, Alysha
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
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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).