绿色航运背景下的泊位分配问题研究
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摘要
随着人们对全球气候变化的广泛关注,燃油价格的不断上升,以及各国政府和国际组织对船舶废气排放的严格限制,航运公司和港口企业逐渐意识到节能减排对企业生存的重要意义,并纷纷通过各种措施降低船舶、集卡等运输工具的燃油消耗和废气排放,绿色航运时代悄然来临。泊位是港口为船舶提供装卸服务的地方,泊位分配问题关系着港航双方的生产运作,是双方共同践行节能减排的最佳契合点,在泊位分配问题研究领域,一个新的研究分支——绿色泊位分配问题——正在形成。本文旨在为这一新的研究分支贡献理论成果,从运作层面为业界实施绿色航运、建设绿色港口提供理论支持。
本文首先从码头一个企业单独决策的角度研究了面向绿色服务的泊位和岸桥联合调度问题,然后将航运公司的航速控制行为考虑进来,研究了港航协作条件下的绿色泊位分配问题：先是在码头集中决策的环境下研究了考虑船舶燃油消耗和废气排放的泊位分配问题,并将研究成果从非潮汐港扩展到了潮汐港；后又在港航双方分散决策的环境下基于Multi-agent技术研究了绿色泊位分配问题。具体而言,本文的研究工作包括如下四个方面：
首先,研究了面向绿色服务的泊位和岸桥联合调度问题。在模型中,用离港延误时间的凸函数刻画船公司在下一航段追赶船期、加速航行而过多消耗燃油和排放废气带来的不满意情绪,同时用计划期内可用的岸桥总工时限制集卡过多的水平跑动,引导集卡节能减排；为降低求解难度,将混合整数非线性规划模型等价转换为混合整数二阶锥规划模型,并采用分支切割优化工具CPLEX对模型求解,由于在有些实例上分支切割算法存在求解时间过长、内存溢出等问题,文中对混合整数非线性规划模型巧妙分解,基于此设计了外逼近算法；数值实验验证了算法的有效性,并对模型中的关键参数进行了灵敏度分析。
第二、将航运公司的航速控制行为考虑进来,研究了码头集中决策环境下的绿色泊位分配问题。从一个新的VAT (Variable Arrival Time)策略出发,将船舶的抵港时间(航速)看作决策变量,以最小化船舶在航行中的燃油消耗和废气排放、最小化离港延误时间为目标建立了双目标优化模型；为克服计算困难,将混合整数非线性规划模型等价转换为混合整数二阶锥规划模型,同时采用ε-constraint方法求解模型的Pareto有效解；在燃油消耗计算的基础上,还对船舶在航行中的废气(CO2、NOX、SOX、PM)排放进行了定量评估；最后,通过一个后优化过程分析了船舶在港等待期间的废气排放。实验表明,新的VAT策略能在不降低(甚至提高)码头服务水平的情况下有效降低船舶在航行中的燃油消耗和废气排放,同时,也能极大降低船舶在港等待期间的废气排放。
第三、将新的VAT策略从非潮汐港推广到潮汐港,研究了节能减排背景下潮汐港的泊位分配问题。据本文作者所知,这也是第一次研究潮汐海港中集装箱码头的泊位分配问题。先是从潮汐对船舶进出港的影响出发进行建模,为减轻非凸性和非线性带来的求解困难,对模型进行了等价变换。本文还从潮汐港中几个重要的管理问题出发进行了全面的数值实验,实验表明,在潮汐港中实施新的VAT策略,不仅能帮助船公司节能减排,还能有效缓解潮汐对岸边作业的影响,很多时候还可以避免挖掘航道的大兴土木和资金消耗。此外,还给出了潮汐港的离散泊位分配模型,指出其可以应用到散货码头,从两个方面扩展了前人的研究工作。
最后,研究了港航双方分散决策环境下的绿色泊位分配问题。在这一问题中,码头不再是集中决策者,港航双方被看作平等、自治的决策主体。文中基于Multi-agent技术提出了解决方案,并以泊位分配模型的影子价格为基础设计了港航双方的协商机制,为适应潮汐港的应用,还针对潮汐船舶设计了基于几种启发式算法的协商机制；之后讨论了代表码头Agent和船舶Agent各自理性的优化模型和算法,其中,证明了航速优化模型的凸性,并采用Newton法对全局最优值进行搜索；为推广此Multi-agent系统在航运实践中的应用,文中还讨论了船-岸双方各自需做的软硬件部署。
The global concern about climate change, the rapid growth of bunker fuel prices, and the more stringent legislation, of governments and international organizations, on vessel emissions have been conveying the signals of the coming of a new green shipping era. Shipping lines and ports are therefore making great efforts to reduce fuel consumption and emissions from both vessels and container trucks. The berth is the place in the port where vessels moor for the service of loading and unloading their cargoes. The berth allocation problem (BAP) is thus the business operation interface of the shipping line and the port, which also provides the best chance to coordinate both parties'decisions on energy saving and emission reduction. In fact, a new research stream, named green berth allocation problem (GBAP), is forming in the field of BAP. This dissertation aims to contribute some theoretical studies to this new research stream, and to theoretically support the implementation of green shipping and the construction of green ports.
This dissertation studies the GBAP in three decision contexts:(a) The terminal constructs the berth plan without considering the speed optimization of the vessels;(b) The speed optimization problem (SOP) is integrated into the BAP, and the terminal is regarded as the sole centralized decision maker; and (c) The terminal and the vessel are treated as separate autonomic agents. They make their own decisions in a decentralized context and coordinate with each other via a dedicatedly-designed negotiation mechanism. The latter two contexts are both driven by port-shipping coordination. More specifically, the studies in this dissertation can be summarized as follows.
First, in the first decision context mentioned above, the berth allocation and quay crane assignment problem with green considerations is addressed. In the mathematical model, a convex objective function of the departure delay time is employed to describe the dissatisfaction of the shipping line resulted from excessive fuel consumption and vessel emissions due to the speed-up in the sailing leg to next port. Also the emissions from the container trucks are implicitly considered by imposing a constraint on the available working hours of the quay cranes in the planning horizon. To overcome the computational intractability and the optimality absence, the mixed integer nonlinear programming (MINLP) model is equivalently transformed to a mixed integer second order cone programming (MISOCP) model, which is solved by the branch and cut (B&C) solver CPLEX. Since the B&C algorithm is time-consuming and runs out of memory for some test instances, an outer approximation (OA) algorithm is put forward based on a novel decomposition towards the original MINLP model. Through numerical experiments, the efficiency and effectiveness of the OA algorithm are verified, and the sensitivity analysis on the key parameters is conducted.
Second, the BAP and the SOP are integrated into a comprehensive optimization model, in which the terminal is the centralized decision maker assuming that the vessels will accept the arrival times suggested by the terminal. By adopting a new berthing strategy called VAT (Variable Arrival Time) and regarding the arrival times of the vessels as decision variables, a bi-objective optimization model is formulated, which aims to minimize the departure delay time of the vessels, and to minimize the fuel consumption and the vessel emissions in the sailing period. To run over the barrier of the nonlinear complexity introduced by fuel calculation, the model is cast as a MISOCP one. Meanwhile, the ε-constraint approach is employed to generate the Pareto efficient solutions of the model. Furthermore, the vessel emission calculation (in sailing periods) is conducted with the widely-used emission factors. Besides, vessel emissions in mooring periods are also analyzed through a post-optimization phase on waiting time. Experimental results demonstrate that the VAT strategy is competent to significantly reduce fuel consumption and vessel emissions, while simultaneously retaining the service level of the terminal.
Third, the VAT strategy is extended to the tidal seaport, and the GBAP in the tidal seaport is studied. As far as we know, this is the first study on the BAP of the container terminal in the tidal seaport. The mathematical model reflects the influence of the tide on the sailing of vessels in the navigation channel, and is equivalently transformed to weaken the potential nonconvexity and the nonlinearity involved. Extensive numerical experiments are conducted to answer several interesting questions arising from the management of the tidal seaport. Apart from the economic benefit of the reduction of fuel expenses and the environmental benefit of emission mitigation, experimental results also show that the VAT strategy can substantially ease the influence of the tide on the seaside operations in the container terminal, and is an applicable substitute for deepening the navigation channel in the tide port. Moreover, a model on the BAP with discrete berth space is also formulated, which contributes to the literature on the BAP in the tidal bulk port in two aspects.
Last, the GBAP in the decentralized decision context is considered, in which the terminal and the shipping line are regarded as rational but selfish agents.In our solution based on the multi-agent technology, the terminal agent solves its BAP, the vessel agent (the shipping line) optimizes its sailing speed, and the performance of the whole system is improved incrementally through an iterative negotiation procedure based on a dedicatedly-designed mechanism. This study designs the negotiation mechanism for the tide-independent vessels based on the shadow prices derived from the linear programming relaxation of the BAP model, and some heuristics for the tide-dependent vessels. Afterwards, the optimization models and the corresponding algorithms, which reflect the individual rationality of the terminal agent and the vessel agent, are discussed. For the speed optimization model of the vessel agent and the algorithms, some analytical results are introduced in the form of propositions and theorems, and the Newton's method is employed to find the global optima. Besides the experimental results, the issue on how to deploy the multi-agent system with respect to hardware and software is addressed such that the decentralized VAT strategy can be put into practice.
本文首先从码头一个企业单独决策的角度研究了面向绿色服务的泊位和岸桥联合调度问题,然后将航运公司的航速控制行为考虑进来,研究了港航协作条件下的绿色泊位分配问题：先是在码头集中决策的环境下研究了考虑船舶燃油消耗和废气排放的泊位分配问题,并将研究成果从非潮汐港扩展到了潮汐港；后又在港航双方分散决策的环境下基于Multi-agent技术研究了绿色泊位分配问题。具体而言,本文的研究工作包括如下四个方面：
首先,研究了面向绿色服务的泊位和岸桥联合调度问题。在模型中,用离港延误时间的凸函数刻画船公司在下一航段追赶船期、加速航行而过多消耗燃油和排放废气带来的不满意情绪,同时用计划期内可用的岸桥总工时限制集卡过多的水平跑动,引导集卡节能减排；为降低求解难度,将混合整数非线性规划模型等价转换为混合整数二阶锥规划模型,并采用分支切割优化工具CPLEX对模型求解,由于在有些实例上分支切割算法存在求解时间过长、内存溢出等问题,文中对混合整数非线性规划模型巧妙分解,基于此设计了外逼近算法；数值实验验证了算法的有效性,并对模型中的关键参数进行了灵敏度分析。
第二、将航运公司的航速控制行为考虑进来,研究了码头集中决策环境下的绿色泊位分配问题。从一个新的VAT (Variable Arrival Time)策略出发,将船舶的抵港时间(航速)看作决策变量,以最小化船舶在航行中的燃油消耗和废气排放、最小化离港延误时间为目标建立了双目标优化模型；为克服计算困难,将混合整数非线性规划模型等价转换为混合整数二阶锥规划模型,同时采用ε-constraint方法求解模型的Pareto有效解；在燃油消耗计算的基础上,还对船舶在航行中的废气(CO2、NOX、SOX、PM)排放进行了定量评估；最后,通过一个后优化过程分析了船舶在港等待期间的废气排放。实验表明,新的VAT策略能在不降低(甚至提高)码头服务水平的情况下有效降低船舶在航行中的燃油消耗和废气排放,同时,也能极大降低船舶在港等待期间的废气排放。
第三、将新的VAT策略从非潮汐港推广到潮汐港,研究了节能减排背景下潮汐港的泊位分配问题。据本文作者所知,这也是第一次研究潮汐海港中集装箱码头的泊位分配问题。先是从潮汐对船舶进出港的影响出发进行建模,为减轻非凸性和非线性带来的求解困难,对模型进行了等价变换。本文还从潮汐港中几个重要的管理问题出发进行了全面的数值实验,实验表明,在潮汐港中实施新的VAT策略,不仅能帮助船公司节能减排,还能有效缓解潮汐对岸边作业的影响,很多时候还可以避免挖掘航道的大兴土木和资金消耗。此外,还给出了潮汐港的离散泊位分配模型,指出其可以应用到散货码头,从两个方面扩展了前人的研究工作。
最后,研究了港航双方分散决策环境下的绿色泊位分配问题。在这一问题中,码头不再是集中决策者,港航双方被看作平等、自治的决策主体。文中基于Multi-agent技术提出了解决方案,并以泊位分配模型的影子价格为基础设计了港航双方的协商机制,为适应潮汐港的应用,还针对潮汐船舶设计了基于几种启发式算法的协商机制；之后讨论了代表码头Agent和船舶Agent各自理性的优化模型和算法,其中,证明了航速优化模型的凸性,并采用Newton法对全局最优值进行搜索；为推广此Multi-agent系统在航运实践中的应用,文中还讨论了船-岸双方各自需做的软硬件部署。
The global concern about climate change, the rapid growth of bunker fuel prices, and the more stringent legislation, of governments and international organizations, on vessel emissions have been conveying the signals of the coming of a new green shipping era. Shipping lines and ports are therefore making great efforts to reduce fuel consumption and emissions from both vessels and container trucks. The berth is the place in the port where vessels moor for the service of loading and unloading their cargoes. The berth allocation problem (BAP) is thus the business operation interface of the shipping line and the port, which also provides the best chance to coordinate both parties'decisions on energy saving and emission reduction. In fact, a new research stream, named green berth allocation problem (GBAP), is forming in the field of BAP. This dissertation aims to contribute some theoretical studies to this new research stream, and to theoretically support the implementation of green shipping and the construction of green ports.
This dissertation studies the GBAP in three decision contexts:(a) The terminal constructs the berth plan without considering the speed optimization of the vessels;(b) The speed optimization problem (SOP) is integrated into the BAP, and the terminal is regarded as the sole centralized decision maker; and (c) The terminal and the vessel are treated as separate autonomic agents. They make their own decisions in a decentralized context and coordinate with each other via a dedicatedly-designed negotiation mechanism. The latter two contexts are both driven by port-shipping coordination. More specifically, the studies in this dissertation can be summarized as follows.
First, in the first decision context mentioned above, the berth allocation and quay crane assignment problem with green considerations is addressed. In the mathematical model, a convex objective function of the departure delay time is employed to describe the dissatisfaction of the shipping line resulted from excessive fuel consumption and vessel emissions due to the speed-up in the sailing leg to next port. Also the emissions from the container trucks are implicitly considered by imposing a constraint on the available working hours of the quay cranes in the planning horizon. To overcome the computational intractability and the optimality absence, the mixed integer nonlinear programming (MINLP) model is equivalently transformed to a mixed integer second order cone programming (MISOCP) model, which is solved by the branch and cut (B&C) solver CPLEX. Since the B&C algorithm is time-consuming and runs out of memory for some test instances, an outer approximation (OA) algorithm is put forward based on a novel decomposition towards the original MINLP model. Through numerical experiments, the efficiency and effectiveness of the OA algorithm are verified, and the sensitivity analysis on the key parameters is conducted.
Second, the BAP and the SOP are integrated into a comprehensive optimization model, in which the terminal is the centralized decision maker assuming that the vessels will accept the arrival times suggested by the terminal. By adopting a new berthing strategy called VAT (Variable Arrival Time) and regarding the arrival times of the vessels as decision variables, a bi-objective optimization model is formulated, which aims to minimize the departure delay time of the vessels, and to minimize the fuel consumption and the vessel emissions in the sailing period. To run over the barrier of the nonlinear complexity introduced by fuel calculation, the model is cast as a MISOCP one. Meanwhile, the ε-constraint approach is employed to generate the Pareto efficient solutions of the model. Furthermore, the vessel emission calculation (in sailing periods) is conducted with the widely-used emission factors. Besides, vessel emissions in mooring periods are also analyzed through a post-optimization phase on waiting time. Experimental results demonstrate that the VAT strategy is competent to significantly reduce fuel consumption and vessel emissions, while simultaneously retaining the service level of the terminal.
Third, the VAT strategy is extended to the tidal seaport, and the GBAP in the tidal seaport is studied. As far as we know, this is the first study on the BAP of the container terminal in the tidal seaport. The mathematical model reflects the influence of the tide on the sailing of vessels in the navigation channel, and is equivalently transformed to weaken the potential nonconvexity and the nonlinearity involved. Extensive numerical experiments are conducted to answer several interesting questions arising from the management of the tidal seaport. Apart from the economic benefit of the reduction of fuel expenses and the environmental benefit of emission mitigation, experimental results also show that the VAT strategy can substantially ease the influence of the tide on the seaside operations in the container terminal, and is an applicable substitute for deepening the navigation channel in the tide port. Moreover, a model on the BAP with discrete berth space is also formulated, which contributes to the literature on the BAP in the tidal bulk port in two aspects.
Last, the GBAP in the decentralized decision context is considered, in which the terminal and the shipping line are regarded as rational but selfish agents.In our solution based on the multi-agent technology, the terminal agent solves its BAP, the vessel agent (the shipping line) optimizes its sailing speed, and the performance of the whole system is improved incrementally through an iterative negotiation procedure based on a dedicatedly-designed mechanism. This study designs the negotiation mechanism for the tide-independent vessels based on the shadow prices derived from the linear programming relaxation of the BAP model, and some heuristics for the tide-dependent vessels. Afterwards, the optimization models and the corresponding algorithms, which reflect the individual rationality of the terminal agent and the vessel agent, are discussed. For the speed optimization model of the vessel agent and the algorithms, some analytical results are introduced in the form of propositions and theorems, and the Newton's method is employed to find the global optima. Besides the experimental results, the issue on how to deploy the multi-agent system with respect to hardware and software is addressed such that the decentralized VAT strategy can be put into practice.
引文
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