scholarly journals A Two-Echelon Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations

2021 ◽  
Vol 11 (22) ◽  
pp. 10779
Author(s):  
Dan Wang ◽  
Hong Zhou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Efficiency ◽  
Programming Model ◽  
Time Windows ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Fixed Cost ◽  
Routing Problem

Driven by the new laws and regulations concerning the emission of greenhouse gases, it is becoming more and more popular for enterprises to adopt cleaner energy. This research proposes a novel two-echelon vehicle routing problem consisting of mixed vehicles considering battery swapping stations, which includes one depot, multiple satellites with unilateral time windows, and customers with given demands. The fossil fuel-based internal combustion vehicles are employed in the first echelon, while the electric vehicles are used in the second echelon. A mixed integer programming model for this proposed problem is established in which the total cost, including transportation cost, handling cost, fixed cost of two kinds of vehicles, and recharging cost, is minimized. Moreover, based on the variable neighborhood search, a metaheuristic procedure is developed to solve the problem. To validate its effectiveness, extensive numerical experiments are conducted over the randomly generated instances of different sizes. The computational results show that the proposed metaheuristic can produce a good logistics scheme with high efficiency.

scholarly journals Spatiotemporal-Dependent Vehicle Routing Problem Considering Carbon Emissions

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Ziqi Liu ◽  
Yeping Chen ◽  
Jian Li ◽  
Dongqing Zhang
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Travel Speed ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Adaptive Genetic Algorithm ◽  
Local Optimum ◽  
Routing Problem

Aiming to improve the timeliness of logistics distribution and render the optimized route scheme effective under the real traffic network, we study the green vehicle routing problem with dynamic travel speed from both dimensions of time and space. A discrete formulation is proposed to calculate the travel time based on periods and arcs, which allows a vehicle to travel across an arc in multiple periods. Then, we establish a mixed-integer nonlinear programming model with minimum distribution costs including transportation costs, carbon emissions costs, and penalty costs on earliness and tardiness. A hybrid adaptive genetic algorithm with elite neighborhood search is developed to solve the problem. In the algorithm, a neighborhood search operator is employed to optimize elite individuals so that the algorithm can stimulate the intensification and avoid falling into a local optimum. Experimental instances are constructed based on benchmark instances of vehicle routing problem. The numerical results indicate that the proposed algorithm is rather effective in global convergence. Compared with the routing schemes in which travel speed merely varies with time periods or locations, the vehicle route optimized on spatiotemporal-varying speed outperforms them in terms of carbon emissions and timeliness. The research can provide a scientific and reasonable method for logistics enterprises to plan the vehicle schedule focusing on spatiotemporal-dependent speed of the road network.

scholarly journals A model for the time dependent vehicle routing problem with time windows under traffic conditions with intelligent travel times

2021 ◽  
Author(s):  
Saeed Khanchehzarrin ◽  
Maral Shahmizad ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Peiman Ghasemi
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Time Windows ◽  
Time Dependent ◽  
Mixed Integer ◽  
Travel Times ◽  
Routing Problem ◽  
Traffic Conditions

A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the travel time between any two nodes depends on traffic conditions and is considered to be a function of vehicle departure time. Depending on working hours, the route between any two nodes has a unique traffic parameter. We consider each working day to be divided into several equal and large intervals, termed as a scenario. Here, allowing for long distances between some of the nodes, travel time may take more than one scenario, resulting in resetting the scenario at the start of each large interval. This repetition of scenarios has been used in modeling and calculating travel time. A tabu search optimization algorithm is devised for solving large problems. Also, after linearization, a number of random instances are generated and solved by the CPLEX solver of GAMS to assess the effectiveness of our proposed algorithm. Results indicate that the initial travel time is estimated appropriately and updated properly in accordance with to the repeating traffic conditions.

scholarly journals A mixed-integer linear programming model for the selective full-truckload multi-depot vehicle routing problem with time windows

2021 ◽  
Vol 10 (4) ◽  
pp. 471-486 ◽  
Author(s):  
Karim EL Bouyahyiouy ◽  
Adil Bellabdaoui
Keyword(s):  
Linear Programming ◽  
Vehicle Routing ◽  
Integer Linear Programming ◽  
Vehicle Routing Problem ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Time Windows ◽  
Mixed Integer ◽  
Data Set ◽  
Routing Problem

This article has studied a full truckload transportation problem in the context of an empty return scenario, particularly an order selection and vehicle routing problem with full truckload, multiple depots and time windows (SFTMDVRPTW). The aim is to develop a solution where a set of truck routes serves a subset of selected transportation demands from a number of full truckload orders to maximize the total profit obtained from those orders. Each truck route is a chain of selected demands to serve, originating at a departure point and terminating at an arriving point of trucks in a way that respects the constraints of availability and time windows. It is not mandatory to serve all orders, and only the profitable ones are selected. In this study, we have formulated the SFTMDVRPTW as a mixed-integer linear programming (MILP) model. Finally, Computational results are conducted on a new data set that contains thirty randomly generated problem instances ranging from 16 to 30 orders using the CPLEX software. The findings prove that our model has provided good solutions in a reasonable time.

scholarly journals Vehicle Routing Problem with Transshipment: Mathematical Model and Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Thanapat Leelertkij ◽  
Parthana Parthanadee ◽  
Jirachai Buddhakulsomsiri
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Retail Stores ◽  
Routing Problem ◽  
Hybrid Heuristics ◽  
New Variant ◽  
Problem Instances

This paper presents a new variant of vehicle routing problem with paired transshipment demands (VRPT) between retail stores (customers) in addition to the regular demand from depot to retail stores. The problem originates in a real distribution network of high-end retail department stores in Thailand. Transshipment demands arise for one-order-per-season expensive items, whose inventories at the depot may become shortage after the middle of a season, while they remain available at some retail stores. A transshipment demand is a request for items that need to be picked up from a specific store that has the items and delivered to the store that requests the items. The objective of solving the VRPT is to find delivery routes that can satisfy both regular demands and transshipment demands in the same routes without incurring too much additional transportation distance. A mixed integer linear programming model is formulated to represent the VRPT. Six small problem instances are used to test the model. A hybrid threshold accepting and neighborhood search heuristic is also developed to solve large problem instances of VRPT. The heuristic is further extended to include a forbidden list of transshipment demands that should not be included in the same routes. The purpose is to prevent incurring too much additional distance from satisfying transshipment demands. With the forbidden list, the problem becomes vehicle routing problem with optional transshipment demands (VRPOT). Computational testing shows promising results that indicate effectiveness of the proposed hybrid heuristics as well as the forbidden list.

Model and Algorithm for Vehicle Routing Problem with Time Windows and a Limited Number of Vehicles

2012 ◽  
Vol 482-484 ◽  
pp. 2322-2326 ◽  
Author(s):  
Yong Ji Jia ◽  
Chang Jun Wang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Programming Model ◽  
Search Algorithm ◽  
Time Windows ◽  
Real Life ◽  
Mixed Integer ◽  
Routing Problem ◽  
Number Of Customers

In this paper, a useful variant of the vehicle routing problem, Vehicle Routing Problem with Time Windows and a limited number of vehicles (m-VRPTW) is given. The problem is to serve a number of customers at minimum cost by using a limited number of vehicles, without violating the time window constraint and the vehicle capacity constraint. The feasible solution of m-VRPTW may contain some unserved customers and third-party vehicles, such as taxies, are hired to serve these unserved customers. The mixed integer programming model of m-VRPTW is proposed and a two-phase algorithm based on insertion algorithm and tabu search algorithm is proposed to solve it. Experimental results show that our algorithm can yield effective and efficient solution and be capable of dealing with the m-VRPTW problems in real life conditions.

A Multi-Period Evacuation Vehicle Routing Problem Model

2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
High Water ◽  
Mixed Integer ◽  
Routing Problem ◽  
Problem Model ◽  
Proposed Model ◽  
Evacuation Routing

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.

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