Mingyao Qi

A generalized multi-depot vehicle routing problem with replenishment based on LocalSolver

In this paper, we consider the multi depot heterogeneous vehicle routing problem with time windows in which vehicles may be replenished along their trips. Using the modeling technique in a new-generation solver, we construct a novel formulation considering a rich series of constraint conditions and objective functions. Computation results are tested on an example comes from the real-world application and some cases obtained from the benchmark problems. The results show the good performance of local search method in the efficiency of replenishment system and generalization ability. The variants can be used to almost all kinds of vehicle routing problems, without much modification, demonstrating its possibility of practical use.

Fuel Consumption Optimization Model for the Multi-Period Inventory Routing Problem

In the traditional multi-period inventory routing problem (MIRP), traveling distance is considered as the only measurement of vehicles’ variable transportation cost; however, it is in fact the fuel consumption cost, not the distance, which is the greater concern. This paper evaluates vehicles’ variable transportation cost by fuel consumption, which is influenced by distance, load, and fuel price. It presents an integer program to formally characterize the fuel consumption considered MIRP (FCMIRP), which can help enterprises obtain a more accurate tradeoff between transportation and inventory costs. It also benefits the environment, because reducing fuel consumption will curb carbon dioxide (CO2) emissions. Valid inequalities are added to strengthen the model and use a branch-and-cut algorithm. Computational tests indicate that the FCMIRP can decrease fuel consumption and total cost over the traditional model. Factors that influence the results of FCMIRP are also discussed.

Competitive facility location problem with foresight considering service distance limitations

Abstract This paper presents a bi-level, nonlinear, integer programming model for the competitive facility location problem with foresight. The developed model’s objective is to maximize the leader’s market share while also taking into consideration the follower’s response. In the classical competitive facility location model, it is assumed that the facility competes for all customers, no matter how far away they are. Instead, this paper considers a new kind of customer behavior in which people only patronize facilities within a range they feel is convenient, which is more realistic than the existing models. To solve the model, a two-stage hybrid tabu search algorithm is proposed. A set of randomly generated instances are presented and analyzed statistically in order to illustrate the effectiveness of the proposed algorithm. The results indicate that the proposed algorithm provides an effective means to solve the problems and that service distance is proved to be a significant factor in the model.

Formulation of service network design with time requirements to schedule heterogeneous fleet

To satisfy specific real-life demand of freight transportation carriers, this paper proposes an arc-based formulation for service network design with time requirements to schedule heterogeneous fleet. The computational study indicates the validity of the formulation both academically and practically. The results shows that heterogeneous fleet is essential to tactical planning for increasing the loading rate of vehicles and reducing the waste of resources.

The Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations

As battery electric vehicles are more and more popular nowadays, this paper presents an Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations to extend their range of application. In the problem, a fleet of the same kind of battery electric vehicles will fulfill the demand of all customers within the serving area by means of delivery operation with a fixed battery swapping time. Time windows of customers are taken into consideration. Small instances of benchmark problem are extended and testified by Gurobi optimizer. Two models of swapping and recharging pattern are compared with the same parameters, verifying that the swapping mode can decrease the number of vehicles.

General Metaheuristic Algorithm for a Set of Rich Vehicle Routing Problems

This paper studies a set of rich vehicle routing problems incorporating various complexities found in real-life applications. The rich vehicle routing problem considers simultaneously four multiple constraints: multiple depots, multiple time windows, multiple trips, and multiple vehicle types. A metaheuristic algorithm called the general vehicle routing algorithm, based on the skewed variable neighborhood search, was designed to address the problem of any combination on five features. A slice of operators and heuristic approaches developed for the specific constraints is embedded in the general vehicle routing algorithm. Six combination vehicle routing problem types were investigated. The computational results demonstrated that the proposed algorithm is competitive for both benchmark instances and generated instances in accuracy of solution and computational time.

Investigating Surrogate Point-Based Modeling Approach for Covering Continuous Spatial Demand

The facility location problem (FLP) has broad applications in transportation, ranging from siting electric vehicle charging stations to positioning emergency vehicles. The spatial facility location problem (SFLP) considers continuous demand of a region where facilities can be placed anywhere. One of the approaches to solving the SFLP is to aggregate the demand into discrete points first and then solve the corresponding point-based FLP as a surrogate model. The model performance, however, is measured by the percentage of the continuous space actually covered. The solution to the classic FLP is often not unique. In this paper, we explore how the behavior of the solution to the FLP would affect the quality of the coverage to the spatial demand. We examine in detail the property of the surrogate model and identify the key contributing factor that would affect the quality of the solution to the original coverage problem for covering continuous spatial demand. Our goal is to find a surrogate model that is detailed enough to capture all the key elements of the problem and achieve the desired accuracy level, yet has the size that can be handled by the existing computing power.

Stochastic mobile facility routing and scheduling problem

We consider the mobile facility routing and scheduling problem with stochastic demand (MFRSPSD). MFRSPSD simultaneously determines the route and schedule of a fleet of mobile facilities which serve customers with uncertain demand in order to minimize the total cost generated over the planning horizon. The problem is formulated as a two-stage stochastic programming model, in which the first stage decision deals with the temporal and spatial movement of the MFs and the second stage handles how MFs serve customer demands. An algorithm based on the multicut version of L-shaped method is developed. The computational results show that the algorithm yields high quality upper and lower bounds within reasonable computation time for medium scale problems.

Optimal boundaries for class-based Automated Storage/Retrieval systems considering the acceleration/deceleration of the storage and retrieval machine

The optimal boundaries for class-based Automated Storage and Retrieval systems (AS/RSs) are derived while the acceleration/deceleration of the storage and retrieval(S/R) machine are considered. A solution procedure is developed which required only two mutually independent one-dimensional search procedures. The results show that the effect of dividing region I near to I/O point by partitioning the rack into two parts based its shape factor, has a better performs to reduce the expected travel time than the effect of dividing region II far from I/O point. Moreover, it is also shown that most of the potential improvement can be realized only by dividing the region I of warehouse into a small number of sub-regions.