Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load

Abstract

Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL) are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting Genetic Algorithm II (NSGA-II) is designed to obtain candidate transport paths. Second, with analysis on the operating process of vehicles with hazardous materials in FCL, the vehicle scheduling problem is converted to Vehicle Routing Problem with Time Windows (VRPTW). A problem-solving method based on estimation of distribution is adopted. A transport timetable for all vehicles based on their transport paths is calculated, with participation of the decision-makers. A visual vehicle scheduling plan is presented for the decision-makers. Last, two examples are used to test the method proposed in this study: distribution of hazardous materials in a small-scale test network and distribution of oil products for sixteen gas stations in the main districts of Lanzhou city. In both examples, our method is used to obtain the path selection and vehicle scheduling plan, proving that validity of our method is verified.

Model construction of material distribution system based on digital twin

“…Formula (2) indicates that the difference between the delivery vehicle and the time window is the smallest when it arrives at the corresponding station; Formula (3) indicates that the total distance traveled by the distribution vehicle when performing the distribution task is the shortest; Formula (4) indicates that all distribution vehicles start from the distribution center and return to the distribution center after performing the distribution task; Formula (5) indicates that the materials loaded by all distribution vehicles cannot exceed the maximum capacity; Formula (6) indicates that the number of distribution stations does not exceed the total number of stations; Formula (7) indicates that each station should be distributed; Formula (8) indicates that each station can only be distributed by one vehicle; Formula (9) indicates that the delivery vehicle arrives earlier than the specified time window or later than the specified time window, and can only be one of them.…”

“…For the research of material distribution route, Chai, H et al designed a two-stage multi-objective optimization algorithm for the whole container logistics distribution path planning of dangerous goods. This method can obtain the Pareto optimal iteration faster for the small-scale path problem [6]. Tang, s designed an improved hybrid algorithm based on Hopfield neural network and SA algorithm to improve the optimization and robustness of the algorithm.…”

Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game

“…Moreover, we recommend that the risk-averse decision makers do not distance more than 24% of the optimal solution for the second objective because no significant improvement in the risk objective will occur. The literature on hazmat routing-scheduling shows that Zografos and Androutsopoulos ( 2004), Chang et al (2005), Zografos and Androutsopoulos ( 2008), Androutsopoulos and Zografos (2010), Pradhananga et al (2014a), Chai et al (2017), Fang et al (2017 investigated the tradeoff between the risk and cost objectives without further analysis on the risk and cost relationship. However, our tradeoff curve is similar to those presented by Androutsopoulos and Zografos (2010), Chai et al (2017), Fang et al (2017,…”

A Novel Approach to Site Selection: Collaborative Multi-Criteria Decision Making through Geo-Social Network (Case Study: Public Parking)

“…Today, due to the widespread use of the automotive, almost all large cities experience public parking unavailability. In fact, one of the issues that comes up to solve the traffic problem is the right choice for public parking [6,7]. Therefore, it is necessary to study a previous approach to obtain the most advantageous site selection for public parking.…”