Mixed-case palletization for warehouse management systems

托盘搭建是仓储行业的核心功能之一。托盘是从仓库到零售店的标准送货形式。所有仓库管理系统的目标是建立良好的托盘，尊重运输要求，如稳定性，以及零售偏好，如物品族分组。 混合托盘优化是Dematic Limited与滑铁卢优化实验室(WatOpt)的Samir Elhedhli教授和Fatma Gzara教授之间的NSERC Engage应用程序的主题。 在Engage项目下进行的研究侧重于两个目标：了解托盘建造的主要挑战；调查关于现有解决方法的文献；对最有希望的方法进行比较研究。 目前的项目以Engage项目中的研究成果为基础。本研究项目的目标是为三维装箱问题和混合情况托盘优化问题开发模型、求解方法和数据驱动的优化方法。虽然这些问题很容易陈述，但它们的优化却极具挑战性。我们的目标是提出、实施和测试一套复杂的解决方法来解决混合情况托盘优化问题，同时结合一些设计要求，如家庭组、订单偏好、脆性限制和求解速度。

Pallet building is one of the warehousing industry's core functions. Pallets are the standard form of delivery from warehouses to retail stores. Building good pallets that respect transportation requirements such as stability, as well as retail preferences such as item family groupings is a goal of all warehouse management systems. Mixed-case pallet optimization was the subject of an NSERC Engage application between Dematic Limited and Professor Samir Elhedhli and Professor Fatma Gzara from Waterloo's Optimization Lab (WatOpt). The research conducted under the Engage project focused on two objectives: developing an understanding of the major challenges of pallet building; surveying the literature on available solution methodologies; and performing a comparative study of the most promising methodologies. The current project builds on the research findings in the Engage project. The goal of this research project is to develop models, solution methodologies, and data-driven optimization approaches for the 3D bin packing problem and the mixed-case pallet optimization problem. While the problems are easy to state, their optimization is extremely challenging. We aim to propose, implement, and test a set of sophisticated solution approaches to solve the mixed case pallet optimization problem while incorporating several design requirements such as family groups, order preferences, fragility restrictions, and speed of solution.