Budipriyanto, Adi (2018) Kerjasama Pemanfaatan Prasarana dan Sarana Terminal Dalam Upaya Mengurangi Waktu Pelayanan Kapal Di Terminal Peti Kemas. Doctoral thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Berth allocation problem merupakan permasalahan yang kompleks karena adanya faktor ketidakpastian (uncertainty) yang menyebabkan kedatangan kapal di pelabuhan sulit untuk diprediksi dan seringkali terlambat dari jadwal yang telah ditentukan. Keterlambatan kedatangan kapal mengakibatkan sumber daya yang sudah dipersiapkan menjadi menganggur. Operator terminal harus menyusun jadwal ulang untuk mengalokasikan kapal yang mengalami keterlambatan. Apabila sumber daya tidak tersedia maka kapal harus menunggu (antri) sampai dermaga tersedia. Berth allocation tidak semata-mata hanya mengalokasikan kapal ke dermaga, tetapi juga mengalokasikan sumber daya lainnya seperti crane, yard, RTG, dan alat transportasi. Untuk pelabuhan yang memiliki lebih dari satu terminal yang dioperasikan oleh operator berbeda dimana setiap terminal menerapkan sistem windows slot, setiap terminal memiliki potensi pada saat yang sama di satu terminal terjadi kekurangan (shortage) dan terminal lain terjadi kelebihan (surplus) sumber daya. Oleh karena itu dibutuhkan strategi untuk menghadapi kondisi tersebut. Salah satu strategi yang diusulkan adalah dengan melakukan kerja sama atau kolaborasi. Pada kondisi eksisting shipping lines yang memiliki windows slot di satu terminal hanya bisa berthing dan bongkar muat menggunakan sumber daya yang dimiliki terminal tersebut. Apabila seluruh dermaga dan sumber daya di terminal tersebut sedang digunakan, maka kapal yang datang harus menunggu dan antri sampai dermaga tersedia, meskipun di terminal lain terdapat dermaga yang tidak digunakan, demikian juga sebaliknya. Strategi kolaborasi memungkinkan setiap kapal bisa berthing di setiap terminal meskipun kapal tersebut memiliki windows di terminal yang berbeda. Dalam penelitian ini dikembangkan model simultaneous berth allocation problem dengan strategi kolaborasi. Karena sistem yang dimodelkan relatif kompleks dan mengandung unsur ketidakpastian maka dalam studi ini digunakan permodelan discrete event simulation. Beberapa skenario diusulkan dan dipilih skenario terbaik yang terbaik. Skenario ditentukan berdasarkan kombinasi empat faktor, yaitu service order, berth-yard, crane dan strategy, dimana setiap faktor memiliki 2 level. Dengan menggunakan konsep full factorial design (2k factorial design) dihasilkan sebanyak 16 skenario. Skenario pertama merupakan kondisi eksisting yang dijadikan sebagai baseline untuk menentukan skenario terbaik yang ditentukan berdasarkan dua respon, yaitu waktu (waiting time, handling time, turnaround time) dan jumlah kapal yang menunggu. Berdasarkan hasil simulasi diperoleh skenario terbaik dengan kombinasi service order secara menggunakan sistem prioritas, berth-yard secara independent, alokasi crane secara fixed, dan strategi yang digunakan adalah kolaborasi. Hasil simulasi menunjukkan bahwa kolaborasi dapat menciptakan keseimbangan operasi di terminal dengan load tinggi dan terminal dengan load rendah. Waiting time dan turnaround time di terminal dengan load tinggi menjadi lebih pendek, sedangkan di terminal dengan load rendah menjadi lebih panjang. Strategi kolaborasi dapat mengurangi jumlah kapal menunggu hingga 43.82 % per tahun, menurunkan waiting time sebesar 46.82%, dan menurunkan turnaround time sebesar 10.60% per kapal per kedatangan. Kolaborasi menimbulkan terjadinya shifting kapal dan container dari terminal load tinggi ke terminal load rendah. Pergeseran kapal dan container menyebabkan terjadinya perubahan performa finansial bagi kedua terminal. Untuk menghindarkan terjadinya kerugian bagi salah satu pihak, maka dibuat skema profit sharing atau profit redistribution.
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Berth allocation problem is a complex problem because of the uncertainty factor that causes the arrival of the ship in the port is difficult to predict and often the arrival of the ship is late from the schedule.The ship's delays result in the resources already allocated for the vessel cannot be utilized. If the ship comes out of schedule, the terminal operator should re-schedule the ship, so the ship must wait until the berth is available. Berth allocation does not solely allocate ships to berth, but also allocates other resources such as cranes, yards, RTG and transportation. For ports that have more than one terminal operated by different operators and each terminal implements a windows system, each terminal has the potential at the same time in one terminal to have a shortage of resources and another terminal overload (surplus). Strategy is needed to deal with the condition. One of the proposed strategies is to collaborate between terminals. In the existing condition of shipping lines that have windows in one terminal can only berthing, loading and unloading using resources in the terminal. If all the resources at the terminal are in use, the arriving vessel will have to wait and queue until the berth is available, even in other terminals there are unused docks, and vice versa. The collaboration strategy allows each ship to berthing in every terminal even though it has windows in different terminals. The allocation of berth, crane and yard is an interrelated process so that the allocation cannot be done partially or gradually (multiphase). Partial and multiphase solutions are generally accomplished by completing the berth allocation in the first phase, and continued with the crane or yard allocation in the next phase. Multiphase solutions have drawbacks because they do not always result in optimal completion. The allocation of berth, crane and yard is an interrelated process so that the allocation cannot be done partially or gradually (multiphase). Partial and multiphase solutions are generally accomplished by completing the berth allocation in the first phase, and continued with the crane or yard allocation in the next phase. Multiphase solutions have drawbacks because they do not always result in optimal completion. The optimal crane allocation in the second phase can change the optimal berth allocation in the first phase. This research develops simultaneous berth allocation problem model with collaboration strategy. Because the modeled system is relatively complex and contains uncertainty factor, this study uses discrete event simulation model. In this simulation, 16 scenarios were obtained using the full factorial design concept (2k factorial design) from a combination of four factors: service order, berth-yard, crane and strategy, each factor has two levels. The first scenario is an existing condition that is used as a baseline to determine the best scenario. The best scenario is determined based on two responses, namely time (waiting time, handling time, turnaround time) and the number of ships waiting. Simulation results show that collaboration can create a balance of operations in terminals with high load and terminals with low load. Waiting time and turnaround time in terminals with high load becomes shorter, while in terminals with low load becomes longer. The collaboration strategy can reduce the number of ships waiting up to 43.82% per year, while the waiting time is reduced by 46.82%. Turnaround time decreased by 10.60% per ship per arrival. Collaboration creates unavoidable consequences of shifting ships and containers from high load terminals to low load terminals. Shifting vessels and containers leads to changes in financial performance for both terminals. In this research also created profit sharing scheme or profit redistribution to avoid losses for either party.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Additional Information: | RDI 387.164 Adi k |
| Uncontrolled Keywords: | Berth allocation, collaboration,uncertainty |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HE Transportation and Communications > HE311.I4 Urban transportation T Technology > TE Highway engineering. Roads and pavements > TE7 Transportation--Planning |
| Divisions: | Faculty of Industrial Technology > Industrial Engineering > 26001-(S3) PhD Thesis |
| Depositing User: | Adi Budipriyanto |
| Date Deposited: | 07 May 2018 03:52 |
| Last Modified: | 09 Jun 2020 08:00 |
| URI: | http://repository.its.ac.id/id/eprint/51273 |
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