Pengembangan Model Dan Algoritma Heuristik Untuk Mengoptimumkan Pengoperasian Twin Automatic Stacking Crane Pada Automated Container Yard Dengan Mensinkronisasikan Perencanaan Kedatangan Kapal Dan Truk Angkut

Penggunaan Twin Automatic Stacking Crane (Twin ASC) pada terminal peti kemas terotomasi memerlukan strategi pengoperasian yang tepat. Adanya dua ASC dengan ukuran yang sama dapat meningkatkan efektifitas CY (Container Yard). Namun karena ASC memiliki ukuran yang sama maka ASC tidak dapat saling melewati, sehingga memerlukan jarak antar ASC. Pada jarak tersebut salah satu ASC akan berhenti untuk menunggu ASC lainnya menyelesaikan tugasnya dan menjauh. Pengoperasian ASC tergantung oleh jadwal kedatangan kapal dan truk angkut. Jadwal kedatangan kapal bersandar di dermaga untuk melakukan bongkar muat mempengaruhi jadwal penerimaan (receiving) atau jadwal pengiriman (delivery) peti kemas oleh ASC di area waterside. Sedangkan jadwal kedatangan truk angkut memepengaruhi jadwal penerimaan atau jadwal pengiriman peti kemas oleh ASC di area landside. Informasi tersebut sangat mempengaruhi kinerja ASC dan pelayanan dari pelabuhan peti kemas. Karena itu perlu adanya sinkronisasi antara pengoperasian kedua ASC dengan perencanaan kedatangan kapal dan truk. Pada penelitian ini akan dilakukan pengembangan model dan algoritma heuristik untuk mengoptimalkan pengoperasian Twin ASC dengan mensinkronisasikan perencanaan kedatangan kapal dan truk. Tujuan penelitian ini adalah untuk mengembangkan model dan algoritma yang dapat mengoptimumkan pengoperasian ASC dengan menghasilkan total travel distance, total travel time dan biaya energi yang minimum. Hasil percobaan numerik dari model dan algoritma yang dikembangkan menunjukkan bahwa pengoperasian Twin ASC dengan memperhatikan rencana kedatangan truk angkut lebih optimal dibandingkan memperhatikan rencana kedatangan kapal ataupun ketika menggabungkan rencana kedatangan kapal dan truk angkut. Hal ini dikarenakan tingginya variasi kedatangan truk dibandingkan kedatangan kapal, sehingga membutuhkan adanya prioritas alokasi slot agar tidak terjadi pemindahan ulang peti kemas saat truk datang. Dengan demikian dapat menghasilkan total travel distance, total travel time dan biaya energi Twin ASC yang minimum. ========================================================== The usage of Twin Automatic Stacking Crane (Twin ASC) at the automated container terminal require proper operation strategy. The existence of two ASC in one block of CY can improve the effectiveness CY (Container Yard). But because the ASC have the same size, the ASC can not pass each other, thus requiring the distance between ASC. At that distance, one of ASC will stop and wait other ASC completed the task and move away. To facilitate the operation, CY is divided into two sides of the landside (near Gate) and the waterside (near berth). The ASC operation depends on the arrival time of vessel and truck. Berthing time of the vessel for loading and unloading affect the schedule reception (receiving) or delivery schedules (delivery) of containers by ASC in the waterside area. While the arrival time of trucks affect receiving or delivery schedule containers by ASC in the landside area. Operation of ASC in serving containers from a vessel or truck also affect the arrival and departure time of vessel and dump trucks. Such information greatly affect the performance and service of the ASC container port. So we need to synchronize twin ASC operation with the planning of arrival of ships and trucks. In this research will be develop a model and a heuristic algorithm to optimize the operation of Twin ASC by synchronizing the arrival time planning of ships and trucks. The purpose of this research is to develop models and algorithms that can optimize the operation of the ASC to produce a total travel distance, total travel time and minimum energy costs. The results of numerical experiments of models and algorithms developed indicate that the operation of the Twin ASC by observing the planned arrival haul trucks is more optimal than pay attention to the planned arrival or ship when dovetail arrival of the ship and truck transport. This is because the variation in the arrival of the truck than the arrival of the vessel, thus requiring their priority slot allocation in order to prevent the removal of the container when the truck comes. Therefore, it can produce a total travel distance, total travel time and costs Twin ASC minimum energy

Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals

Tesis por compendioDespite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is required at an affordable computational time. Furthermore, decision makers often face different and typically opposing goals, then resulting multi-objective optimization problems. Therefore, approximate techniques from the Artificial Intelligence (AI) field are commonly used to solve the real world problems. The AI techniques provide richer and more flexible representations of real-world (Gomes 2000), and they are widely used to solve these type of problems. AI heuristic techniques do not guarantee the optimal solution, but they provide near-optimal solutions in a reasonable time. These techniques are divided into two broad classes of algorithms: constructive and local search methods (Aarts and Lenstra 2003). They can guide their search processes by means of heuristics or metaheuristics depending on how they escape from local optima (Blum and Roli 2003). Regarding multi-objective optimization problems, the use of AI techniques becomes paramount due to their complexity (Coello Coello 2006). Nowadays, the point of view for planning and scheduling tasks has changed. Due to the fact that real world is uncertain, imprecise and non-deterministic, there might be unknown information, breakdowns, incidences or changes, which become the initial plans or schedules invalid. Thus, there is a new trend to cope these aspects in the optimization techniques, and to seek robust solutions (schedules) (Lambrechts, Demeulemeester, and Herroelen 2008). In this way, these optimization problems become harder since a new objective function (robustness measure) must be taken into account during the solution search. Therefore, the robustness concept is being studied and a general robustness measure has been developed for any scheduling problem (such as Job Shop Problem, Open Shop Problem, Railway Scheduling or Vehicle Routing Problem). To this end, in this thesis, some techniques have been developed to improve the search of optimized and robust solutions in planning and scheduling problems. These techniques offer assistance to decision makers to help in planning and scheduling tasks, determine the consequences of changes, provide support in the resolution of incidents, provide alternative plans, etc. As a case study to evaluate the behaviour of the techniques developed, this thesis focuses on problems related to container terminals. Container terminals generally serve as a transshipment zone between ships and land vehicles (trains or trucks). In (Henesey 2006a), it is shown how this transshipment market has grown rapidly. Container terminals are open systems with three distinguishable areas: the berth area, the storage yard, and the terminal receipt and delivery gate area. Each one presents different planning and scheduling problems to be optimized (Stahlbock and Voß 2008). For example, berth allocation, quay crane assignment, stowage planning, and quay crane scheduling must be managed in the berthing area; the container stacking problem, yard crane scheduling, and horizontal transport operations must be carried out in the yard area; and the hinterland operations must be solved in the landside area. Furthermore, dynamism is also present in container terminals. The tasks of the container terminals take place in an environment susceptible of breakdowns or incidences. For instance, a Quay Crane engine stopped working and needs to be revised, delaying this task one or two hours. Thereby, the robustness concept can be included in the scheduling techniques to take into consideration some incidences and return a set of robust schedules. In this thesis, we have developed a new domain-dependent planner to obtain more effi- cient solutions in the generic problem of reshuffles of containers. Planning heuristics and optimization criteria developed have been evaluated on realistic problems and they are applicable to the general problem of reshuffling in blocks world scenarios. Additionally, we have developed a scheduling model, using constructive metaheuristic techniques on a complex problem that combines sequences of scenarios with different types of resources (Berth Allocation, Quay Crane Assignment, and Container Stacking problems). These problems are usually solved separately and their integration allows more optimized solutions. Moreover, in order to address the impact and changes that arise in dynamic real-world environments, a robustness model has been developed for scheduling tasks. This model has been applied to metaheuristic schemes, which are based on genetic algorithms. The extension of such schemes, incorporating the robustness model developed, allows us to evaluate and obtain more robust solutions. This approach, combined with the classical optimality criterion in scheduling problems, allows us to obtain, in an efficient in way, optimized solution able to withstand a greater degree of incidents that occur in dynamic scenarios. Thus, a proactive approach is applied to the problem that arises with the presence of incidences and changes that occur in typical scheduling problems of a dynamic real world.Rodríguez Molins, M. (2015). Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48545TESISCompendi

Model of Twin Automatic Stacking Crane Operation Strategy with Dynamic Handshake Area in an Automated Container Terminal

This paper proposes a new idea for allocating a handshake area of an automated container yard. A block of automated container yards (CY) consists of two areas, which are the import (waterside) and export (landside) areas. The CY has two major activities (loading and unloading), where both are served by Twin Automatic Stacking Cranes (Twin-ASCs). A handshake area in the middle of the CY serves as a temporary slot for both ASCs. This situation causes an imbalance between the ASCs when the demands of each side differ significantly. Thus, we proposed using a dynamic location of the handshake area corresponding to the proportion demand of export and import containers. We developed a heuristics model and algorithms of ASC’s operations to compare the efficiency of the ASC operations between the fixed and the dynamic location. Based on our model and algorithm, we developed simulation software. Finally, we explored some numerical experiments to compare the performance of both policies in dealing with different export and import demand scenarios. Our result showed that the proposed approach outperformed the existing one in reducing unnecessary ASC movements

Reshuffle minimisation to improve storage yard operations efficiency

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory

Space-sharing Strategies for Storage Yard Management in a Transshipment Hub Port

Ph.DDOCTOR OF PHILOSOPH