集装箱码头泊位、岸桥协调调度优化

The optimization of container berths and shore bridge coordination schedulingMartin EAbstractThe global economic development, the container quickly raised up into exports. Rapid growth of the import and export cargo throughput brings to the container terminal larger benefits at the same time increase the burden of the port, have higher requirements on the terminal operation efficiency. How is the existing equipment of container terminals, reasonable resource allocation and scheduling, is common problem facing the container terminal. Therefore, how to improve the terminal facilities such as the maximum utilization of resources, to meet the increasing port demand, improve their competitive advantage, and has more practical meaning to improve the working efficiency of the container terminal. The main content of this study is berth, gantry cranes and set card co-allocation research, has plans to all ship to the port assignments during mathematical model is established with the target of minimum cost, according to the characteristics of the scale model by genetic algorithm, finally validates the effectiveness of the model.Keywords: System engineering; Water transportation; Gantry cranes allocation; Dynamic scheduling;1 IntroductionContainer terminal logistics is an organic system, made of interactive and dy namic components, such as containers, ships, berths, yards, tracks, quay cranes and yard cranes trucks, labors and communications, in a limited terminal space. It is a complex discrete event dynamic system related to kinds of complicated problems in l ogistics transport field.Berth scheduling (berth allocation) refers to the vessel arrival before or after according to each berth free condition and physical condition of the constraint for ship berthing berth and berthing order. To port berth scheduling optimization research has made important progress, but research is only limited to the single scheduling berth and shore bridge. Of berth scheduling problem in recent years has been based on simple berth scheduling considering more factors, but only for gantry cranes operatingsequence when performing a specific loading and unloading of microscopic optimization. Container ships in the port of time depend on how well the berth scheduling on one hand, on the other hand depends on the completion of tasks of gantry cranes loading and unloading time. Gantry cranes loading and unloading time tasks assigned by the Shore Bridge and gantry cranes scheduling two link form. Gantry cranes allocation is reasonably allocated to the ship to shore bridge. Scheduling is a bridge across the river shore bridge between loading and unloading task scheduling. For container terminal how to out of berth allocation, and collaborative scheduling shore bridge set card effective allocation and the arrangement of the container yard, etc are the main factors influencing the efficiency of port operations.2 Literature reviewBerth, gantry cranes and set card configuration and operation quality directly determines the operational efficiency of container ports. Container port whether can meet customer demand depends on whether the scheduling of a better, affecting the competitiveness of the port. So how to coordinate the three configurations and scheduling caused the wide attention of scholars both at home and abroad. Most experts and scholars in different circumstances port hardware facilities according to the different methods of berth, gantry cranes, set card and etc were studied. In recent years, the berth, shore and set scheduling and allocation problem of study to become a hot topic, scholars in a wide range of further research.2.1 Research on berth allocation problemEdmond will berth allocation problem as queuing theory for the first time, and establish the mathematical model research berth allocation problem. Lai and Shih to adopt rules first come first service berth allocation problem, and design the corresponding heuristic algorithm for the optimization of the mathematical model of the berth allocation, and to obtain the berth allocation to wait for the mooring time, and the average berth utilization indicators for evaluation. Prove the feasibility of obtained berth allocation scheme. Kiin mixed integer programming model is established to study the for large container ship berth allocation problem to determinethe ship docked location and time, the design of simulated annealing algorithm to solve the model. Since then, many scholars study of berth allocation problem scheme compared with Kim. Imai respectively studied and dynamic to static to the port to port berth allocation problem, at the same time the berth allocation in the process of container ship is introduced into the berth time priority, berth allocation was studied for the ship to port. Later, Mr Imai and Sun to adopt continuous geographical space to study the method of continuous berth allocation, established the mathematical model of the minimum vessel waiting time and operation time and coefficient using LaGrange relaxation algorithm to solve. Hansen, considering the schedule and ship docked preference location problems, such as setting the berth scheduling optimization goal for waiting time while minimizing of the ship. At the same time describes what preference position of the ship is. Lee also adopt the rules of first come first service to research into the port ship berth allocation problem, design the corresponding heuristic algorithm to solve the berth allocation model. After this, Lee and ship at the port of all research cycle to overall in the shortest time continuous berth allocation problem for the target research, through random greedy adaptive search algorithm to solve the model.2.2 Research on Shore Bridge factors problemDiazole in 1989 for the first time put forward the concept of gantry cranes scheduling by the author and a mixed integer programming model was established to solve the model to determine the distribution of each ship to the shore bridge. Park and Kim first studied the static to the port of berth and gantry cranes scheduling problem. Lim under interference constraint made the gantry cranes scheduling decisions made by a branch and bound method will be a period of time the latest ship to minimize the departure time of this algorithm ability is limited but simulated annealing method feasible solution can be obtained for the same question then also has used the genetic algorithm and greedy algorithm. Mussel and had to use a more realistic shore bridge resources use function to replace the method of linear hypothesis this paper proposes a new model to improve insufficient corrected simulation in the study of land bridge in front of the interference constraint error and put forward aimproved model than other algorithms are good before fast branch and bound method based on one-way operations. Bierwirth to before 2010 to berth allocation problem, task allocation problem shore bridge, gantry cranes scheduling problem of research literature made a detailed statistics and investigation and study analysis. Ship movement were studied using genetic algorithm reaches the case of fixed alongside berths and gantry cranes scheduling problem, homework and assumes that each ship shore bridge number is fixed, the optimization goal to minimize shipping time in Hong Kong. At present scholars to container terminal berth allocation, gantry cranes scheduling and allocation, set operations such as path planning are detailed studies. They mainly from the perspective of time and economic cost and so on, studies the optimization of container terminal handling operation link research, makes the anticipated goal of optimal. But can be seen from the collected literature at home and abroad, the research of the container terminal although in-depth and meticulous, but there are still insufficient. At present study mainly just to container terminal operation of a single link a job scheduling optimization, or are the two assignments link joint scheduling optimization research. However, container terminal berth allocation, shore bridge distribution and collection card is a complete operating system. If is simply the optimization study of a job link, can only reach a certain optimal operation link, it is difficult to achieve with other assignments link affinity. In the whole container operating system does not make the overall optimal.3 Container terminal operation analyses(1) ChannelChannel is refers to the container ship in the in and out of the container terminal area can satisfy container ships and other water traffic tools (tug, etc.) the requirements of the safe navigation channel.(2) AnchorageAnchorage is used for container ships waiting for berthing of ships docked or for a variety of water homework need water. Main floor including loading and unloading of anchorage, anchorage, shelter, water diversion fault, fault and quarantine and so on, this article proposed tracing refers to anchor it wrong, is to wait for container vesselsinto anchored into the dock before berth waters.(3) BerthBerth is to point to inside the container terminal for container vessels, loading and unloading to the docking area by the sea, for the container ship safety and to meet the need of loading and unloading operation waters and space. Have a certain length of call with berthing waters adjacent quay wall line, referred to as the shoreline. Berth coastline length meet the requirement of container ship loading and unloading and berthing safety distance, depth of berth satisfies the requirement of container ship's draft. Container port berths are mainly divided into two forms. Berth discrete and continuous berths. Discrete berth: container terminal of the coastline of the corresponding berth waters is divided into a number of different lengths of part, at the same time there can be only one ship in a garage to accept service, and any ship berthing of ships in the harbor cannot take up two berths at the same time. Continuous berth: in the container terminal to the coastline of the corresponding vessel berthing water not to break up, to the port container ship in meet the demands of the depth and the captain of the ship to draft cases, can be arbitrary parked in container terminal coastline of the corresponding boundary waters.(4) Gantry cranesLand refers to the coast side of container loading and unloading of the bridge crane, is a special hoisting machinery container wharf apron loading and unloading of containers, container terminal is the only direct contact with berthing ships operating equipment, is one of the most important resources in container terminals and scarce resources. Gantry cranes loading and unloading efficiency and quality of high and low will directly affect the length of the container vessel in operation time, at the same time also affect other container terminal operation link configuration and scheduling. Among them, the land bridge is mainly divided into orbit type gantry cranes and tired gantry cranes. Orbit type gantry cranes, coastline of gantry cranes are all in the same orbit, land bridge between the mobile can not appear the phenomenon such as cross. Tyred Gantry cranes can move than rail type gantry cranes move large range. But at present most of the container terminal mainly Is to use rail type gantry cranes, so inthis paper, we study the land bridge for track type gantry cranes.(5) Set cardSet card can achieve a container in the container yard and onshore bridge between the yard and mobile, collection card is container terminal based on the shipping container truck. Set card according to the different main purpose transportation of container terminal is divided into inside and outside sets card two types of collection card. Set inside the card, is to realize the gantry cranes loading and unloading of containers and a bridge on the stacking yard box between the means of transport. Of all the set inside of the container terminal equipment configuration, scheduling the most complex number of mobile devices. Outside the set of CARDS, sonograms are directly from the port to the shore bridge shipment, or from the shore bridge directly discharging to the container truck outside of a container terminal. (6) YardImport and export container yard is the function of container terminal is used to store the site area, close distance tend to berth. Container terminal will stay according to the purpose of import and export container shipping and shipping time factors such as different, in order to facilitate access to the specified container, the container yard area is divided into multiple box. Due to the container depot in box area position is different, so each box area the distance from the need to load and unload ships size is different. Packing storage location and the distance between the ship dock berths will also affect the level of set card transport time, thus affecting the entire pier loading and unloading efficiency of the system. Can be inferred from this, container storage location is the operation efficiency of container terminals also has a great influence. (7) BridgeThe role of a bridge is similar to the gantry cranes and container loading and unloading transportation tool. Just a bridge job is located in container yard. A bridge, it is within the container yard stacking, move the box and the box operation of loading and unloading equipment. Will set card transport imported within the container stack to the designated container terminal yard box area or take out the box of export containers of area specific location set card, to the specific land bridge loadingoperations.(8) The work facilities such as container yard behindBehind the container yard operation facilities mainly make mouth, control room, maintenance shop, container freight station and other facilities. Describes the mouth, is the container and the container cargo of containers of intersection, and container terminal, both inside and outside dividing line of responsibility. Due to the gate is the container of in and out of the harbor, in the mouth is set between the container of relevant documents, related to container number and seal number and container exterior condition for inspection operations such as link.Berth allocation problems Scope and classification schemeIn berth allocation problems, we are given a berth layout together with a set of v essels that have to be served within a planning horizon. The vessels must be moored within the boundaries of the quay and cannot occupy the same quay space at a time. I n he basic optimization problem, berthing positions and berthing times have to be ass igned to all vessels, such that a given objective function is optimized. A variety of o ptimization models for berth allocation have been proposed in the literature to captur e real features of practical problems. In Bierwirth and Meisel (2010), we have propos ed a scheme for classifying such models according to four attributes, namely a spatia l attribute, a temporal attribute, a handling time attribute, and the performance measur e addressed in the optimization. The values each attribute can take are listed in Fig. 1 Spatial attributeThis attribute concerns the berth layout, which is either a discrete layout (disc), a co ntinuous layout (cont), or a hybrid layout (hybr). In case of disc, the quay is partitio ned into berths and only one vessel can be served at each single berth at a time. In cas e of cont, vessels can berth at arbitrary positions within the boundaries of the quay. F inally, in case hybr, the quay is partitioned into berths, A particular form of a hybrid berth is an indented berth where large vessels can be served from two oppositely loc ated berths. The spatial attribute is extended by item draft, if the BAP-approach addit ionally considers a vessel’s draft when deciding on its berthing position.Temporal attributeThis attribute describes the arrival process of vessels. The attribute reflects static arri vals (stat), dynamic arrivals (dyn), cyclic arrivals (cycl), and stochastic arrival times (s toch). In case of stat, we assume that all vessels have arrived at the port and wait fo r being served. In contrast, in case of dyn, the vessels arrive at individual but determi nistic arrival times imposing a constraint for the berth allocation. In case cycl, he ves sels call at terminals repeatedly in fixed time intervals according to their liner schedu les. In case stoch, the arrival times of vessels are stochastic parameters either define d by continuous random distributions or by scenarios with discrete probability of occ urrence. Cyclic and stochastic arrival times are considered in a number of recent pub lications and, therefore, we have extended the original classification scheme with reg ard to these cases. The temporal attribute is completed by value due, if a due date i s preset for the departure of a vessel or if a maximum waiting time is preset for a ves sel before the service has to start.Handling time attributeThis attribute describes the arrival process of vessels. The attribute reflects static arri vals (stat), dynamic arrivals (dyn), cyclic arrivals (cycl), and stochastic arrival time s (stoch). In case of stat, we assume that all vessels have arrived at the port and wait f or being served. In contrast, in case of dyn, the vessels arrive at individual but deter ministic arrival times imposing a constraint for the berth allocation. In case cycl, h e vessels call at terminals repeatedly in fixed time intervals according to their liner sc hedules. In case stoch, the arrival times of vessels are stochastic parameters either de fined by continuous random distributions or by scenarios with discrete probability o f occurrence. Cyclic and stochastic arrival times are considered in a number of recent publications and, therefore, we have extended the original classification scheme wit h regard to these cases. The temporal attribute is completed by value due, if a due dat e is preset for the departure of a vessel or if a maximum waiting time is preset for a vessel before the service has to start.Handling time attributeThis attribute describes the way how handling times of vessels are given as an input t o the problem. It takes value fix, if the handling times of vessels are known and considered unchangeable. Value pos indicates that handling times depend on the berthin g positions of vessels and value QCAP indicates that handling times are determine d by including QC assignment decisions into the BAP. In case of value QCSP, the ha ndling times are determined by incorporating the QC scheduling within the BAP. I n order to classify the recent literature properly, we have inserted case stoch as a ne w attribute for the scheme. Again, handling times can be subject to either discrete or c ontinuous random distributions. A similar extension of our scheme is also suggeste d by Carlo et al. (2013), who also open it to further sources of influence on vessel han dling times, like operations of transfer vehicles and yard cranes. However, as we har dly find instantiations of these cases in the literature, we refrain from extending the s cheme in further directions.Performance measureThis attribute considers the performance measures of a berth allocation model. Mos t models consider to minimize the port stay time of vessels. This is reached by differ ent objective functions, e.g. when minimizing waiting times before berthing (wait), m inimizing handling times of vessels (hand), minimizing service completion times (co mpl), or minimizing tardy vessel departures (tard). If soft arrival times are given, als o a possible speedup of vessels (speed) is taken into consideration at the expense of a dditional bunker cost. Other models aim at reducing the variable operation cost of a t erminal by optimizing the utilization of resources (res) like cranes, vehicles, berth sp ace, and manpower. An often considered feature is to save horizontal transport capac ity by finding berthing positions for vessels close to the yard, which is why we inclu de this goal by its own value pos. Rarely met performance measures are summarize d by value misc(miscellaneous). The introduced measures are either summed up for al l vessels in the objective function. Alternatively, if the minimization of the measure fo r the worst performing vessel is pursued, i.e. a min–max objective is faced. Vessel-sp ecific priorities or cost rates are shown by weights. Different weights w1 to w4 addre ss combined performance measures.Literature overviewIn the relevant literature, we have found and classified 79 new models for berth allocation, most of them published after 2009. Fig. 2 shows the BAP models devel oped by researchers since 1994 by year of their publication, including also those app roaches reviewed in Bierwirth and Meisel (2010). The figure shows that the interest i n berth allocation started with the early papers of Hoffarth (1994) and Imai, Nagaiw a, and Tat (1997). However, the growth of publications followed the pioneering pape r of Park and Kim (2003), who combined berth allocation and QC assignment for th e first time, and the early survey on container terminal operations by Steenken et a l. (2004). In particular, journal publications scaled up to ten and more per year after 2 010. To the mid of 2014, already 13 new journal papers have been published or acce pted for publication. The continuous effort spend on research in berth allocation confi rms it as a well-established field today, which still shows potential for future researc h.With Table 1, we also provide an overview of the methods that are used for solv ing the BAP models. Note that only the most successful method presented in a pape r appears in the table. It is not surprising that heuristic approaches dominate as the B AP is known to be NP-hard in both, the discrete and the continuous case, see e.g. Li m (1998) and Hansen and Oǧuz (2003). Exact methods are applied in only one fourt h of the approaches, ranging from MILP formulations combined with standard solver s to highly sophisticated branching-based algorithms. Among the heuristic approache s, Genetic Algorithms and Evolutionary Algorithms take the by far largest share wit h 40 percent, see Fig. 3(left). The rest of the methods comprise other meta-heuristic s like Tabu Search and Simulated Annealing as well as problem specific heuristics lik e local search techniques and greedy rules. The richness of BAP models favors meta-heuristic approaches as they allow handling various problem features flexibly. On th e other hand, a systematic evaluation of algorithms is hindered by the strong heterog eneity of BAP models. Although comparing models is definitely necessary for assessi ng the suitability of methods, the comparison of alternative models formulated by dif ferent research groups is just emerging slowly, see Buhrkal, Zuglian, Ropke, Larse n, and Lusby (2011),Umang, Bierlaire, and Vacca (2013), and Imai, Nishimura, an d Papadimitriou (2013). To make this process sustainable, ommonly accepted BAP benchmark instances are needed to provide authors with the opportunity to evaluate the ir work. However, the current benchmarks are either not general enough to fulfill thi s aim or they are merely used in small substreams of the entire research field. Defini ng benchmark problems for general berth allocation problems that fulfill the principle s of comparability, unbiasedness, and reproducibility remains an open topic for futur e research.In the following, we abstain from reviewing all papers listed in Table 1 individu ally. Instead, the next subsection discusses those papers in more detail that contain n ovel features of which we think they might receive particular attention in the future.。