Operations Research, Systems Engineering and Industrial Engineering Commons^™

Glop: Learning Global Partition And Local Construction For Solving Large-Scale Routing Problems In Real-Time, Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li

Research Collection School Of Computing and Information Systems

The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Global and Local Optimization Policies), a unified hierarchical framework that efficiently scales toward large-scale routing problems. GLOP partitions large routing problems into Travelling Salesman Problems (TSPs) and TSPs into Shortest Hamiltonian Path Problems. For the first time, we hybridize non-autoregressive neural heuristics for coarse-grained problem partitions and autoregressive neural heuristics for fine-grained route constructions, leveraging the scalability of the former and the meticulousness of the latter. Experimental results show that GLOP achieves competitive and state-of-the-art real-time performance …

Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao

Research Collection School Of Computing and Information Systems

This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …

Step-Wise Deep Learning Models For Solving Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Routing problems are very important in intelligent transportation systems. Recently, a number of deep learning-based methods are proposed to automatically learn construction heuristics for solving routing problems. However, these methods do not completely follow Bellman's Principle of Optimality since the visited nodes during construction are still included in the following subtasks, resulting in suboptimal policies. In this article, we propose a novel step-wise scheme which explicitly removes the visited nodes in each node selection step. We apply this scheme to two representative deep models for routing problems, pointer network and transformer attention model (TAM), and significantly improve the performance of …

Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou

Research Collection School Of Computing and Information Systems

This article presents the modeling and solution of an extended type of split delivery vehicle routing problem (SDVRP). In SDVRP, the demands of customers need to be met by efficiently routing a given number of capacitated vehicles, wherein each customer may be served multiple times by more than one vehicle. Furthermore, in many real-world scenarios, consumption of vehicles en route is the same as the goods being delivered to customers, such as food, water and fuel in rescue or replenishment missions in harsh environments. Moreover, the consumption may also be in virtual forms, such as time spent in constrained tasks. …

A Multi-Criteria Gis-Based Route Selection Tool For Hazardous Material Transport: Consideration Of Environmental Consequence, Traffic Congestions And Costs, Bahareh Inanloo

FIU Electronic Theses and Dissertations

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year.

The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with …

A Human-Centered Credit-Banking System For Convenient, Fair And Secure Carpooling Among Members Of An Association, H.-S. Jacob Tsao, Magdalini Eirinaki

Faculty Publications

This paper proposes an unconventional carpool-matching system concept that is different from existing systems with four innovative operational features: (F1) The proposed matching system will be used by members of an association and sponsored by the association, e.g., the employees of a company, members of a homeowner association, employees of a shopping center. This expands the scope beyond commute trips. Such associations can also voluntarily form alliances to increase the number of possible carpool partners and geographical reach. (F2) Service provided by a driver or received by a rider incurs credit or debt to a bank centrally and fairly managed …

Evaluation Of Optimization Algorithms For Improvement Of A Transportation Companies (In-House) Vehicle Routing System, Jian Han

Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research

Vehicle routing problem (VRP) is the main issue of the transportation. It is becoming more and more popular. Trucking companies play an important role in the transportation industry. Most trucking companies are developing their own software to make profit. Often, the software is used for routing optimization models to minimize cost because the first work is organized over the road.

Linear Programming and saving heuristics are traditional algorithms for solving the vehicle routing problems. However, none of the companies want to make a decision of routing by calculating with mathematics models in their companies. So the vehicle routing software is …