PortLib Instances for the Port Scheduling Problem.

In the following we present the <em>PortLib</em> instances for the <em>Port Scheduling Problem</em> (PSP), which have been presented in the paper <em>An Adaptive Large Neighbourhood Search Heuristic for Routing and Scheduling Feeder Vessels in Multi-terminal Ports,</em> written by Erik Hellsten, David Sacramento and David Pisinger, and published in <em>European Journal of Operational Research</em>. The repository includes the results for <em>PortLib </em>instances for the <em>Adaptive Large Neighbourhood Search (ALNS)</em> heuristic and the commercial solver <em>CPLEX.</em> Additionally, we further include the results for the <em>Constraint Programming</em> and the <em>ALNS Math-heuristic</em> approaches from the paper <em>Constraint Programming and Local Search Heuristic: A Math-heuristic Approach for Routing and Scheduling Feeder Vessels in Multi-Terminal Ports</em>, written by David Sacramento, Christine Solnon and David Pisinger, and pending for publication in <em>SN Operations Research Forum</em>. Furthermore, this version includes the results for the <em>Constraint Programming</em> models from the paper <em>Integrated Planning of Feeder Vessels at Multi-Terminal Ports</em>, written by David Sacramento and David Pisinger, and pending for publication in <em>4OR</em> <em>- A Quarterly Journal of Operations Research</em>. The PSP represents a new scheduling problem for feeder vessels in multi-terminal ports, which has been defined in close collaboration with the industry. The proposed problem is a General Shop-like problem, and it accounts for most of the practical restrictions faced by the carriers in scheduling the operations. Given a fleet of feeder vessels, which each of them has a number of operations to perform at different terminals, and each terminal can only serve one vessels at a time, the task is to define an operational schedule, i.e. a starting time for each operation, which satisfies the time window and precedence constraints as well as minimises the departure times of the vessels and packs the schedule as tight as possible. The instances are named <strong>PSP.</strong><strong>n.m.r</strong>, where <strong>n</strong> is the number of container-terminals, <strong>m</strong> is the number of vessels, and <strong>r</strong> is the generic name of the scenario. The instances are randomly generated to be realistic, but in addition we ensured that each instance has a feasible solution as well as strove towards that each constraint should have a significant impact. In general, the instances are made to be slightly harder to solve than the problems faced by industry, in order to properly challenge the developed methods, as well as spurring further development.下文将介绍论文《多终端港口驳船调度与路径规划的自适应大邻域搜索启发式算法（An Adaptive Large Neighbourhood Search Heuristic for Routing and Scheduling Feeder Vessels in Multi-terminal Ports）》（作者为Erik Hellsten、David Sacramento与David Pisinger，发表于《European Journal of Operational Research》）中提出的港口调度问题（Port Scheduling Problem，PSP）的<em>PortLib</em>测试集实例。本数据集存储库包含针对<em>PortLib</em>测试集实例，采用自适应大邻域搜索（Adaptive Large Neighbourhood Search，ALNS）启发式算法与商业求解器CPLEX得到的求解结果。此外，本存储库还收录了来自论文《约束规划与局部搜索启发式：多终端港口驳船调度与路径规划的数学启发式方法（Constraint Programming and Local Search Heuristic: A Math-heuristic Approach for Routing and Scheduling Feeder Vessels in Multi-Terminal Ports）》（作者为David Sacramento、Christine Solnon与David Pisinger，目前已被《SN Operations Research Forum》录用待刊）的约束规划（Constraint Programming）与ALNS数学启发式算法的求解结果。进一步地，本版本还包含来自论文《多终端港口驳船集成调度规划（Integrated Planning of Feeder Vessels at Multi-Terminal Ports）》（作者为David Sacramento与David Pisinger，目前已被《4OR - A Quarterly Journal of Operations Research》录用待刊）的约束规划模型求解结果。PSP是一类面向多终端港口驳船调度的新型调度问题，由产业界协同合作定义完成。该问题属于广义车间调度类问题，涵盖了航运企业在调度作业过程中面临的绝大多数实际约束。给定一支驳船船队，每艘驳船均需在不同终端完成若干作业，且每个终端同一时间仅能服务一艘驳船，任务目标为生成一份可执行的调度方案：即为每项作业确定起始时间，该方案需满足时间窗口与优先约束，同时最小化驳船的离港时间，并尽可能紧凑地规划整个调度计划。本测试集实例采用命名格式<strong>PSP.n.m.r</strong>，其中<strong>n</strong>代表集装箱码头数量，<strong>m</strong>代表驳船数量，<strong>r</strong>为场景通用标识。所有实例均通过随机生成以贴合实际场景，同时我们确保每个实例均存在可行解，并尽可能使每项约束都能产生显著影响。总体而言，本测试集的难度略高于产业界实际面临的问题，以便充分验证所提出方法的性能，并推动相关领域的进一步研究与发展。