scholarly journals Multiobjective Quantum Evolutionary Algorithm for the Vehicle Routing Problem with Customer Satisfaction

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
Jingling Zhang ◽  
Wanliang Wang ◽  
Yanwei Zhao ◽  
Carlo Cattani
Keyword(s):  
Customer Satisfaction ◽  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Adaptive Grid ◽  
Solution Set ◽  
Mixed Integer ◽  
Routing Problem ◽  
Nondominated Solution

The multiobjective vehicle routing problem considering customer satisfaction (MVRPCS) involves the distribution of orders from several depots to a set of customers over a time window. This paper presents a self-adaptive grid multi-objective quantum evolutionary algorithm (MOQEA) for the MVRPCS, which takes into account customer satisfaction as well as travel costs. The degree of customer satisfaction is represented by proposing an improved fuzzy due-time window, and the optimization problem is modeled as a mixed integer linear program. In the MOQEA, nondominated solution set is constructed by the Challenge Cup rules. Moreover, an adaptive grid is designed to achieve the diversity of solution sets; that is, the number of grids in each generation is not fixed but is automatically adjusted based on the distribution of the current generation of nondominated solution set. In the study, the MOQEA is evaluated by applying it to classical benchmark problems. Results of numerical simulation and comparison show that the established model is valid and the MOQEA is effective for MVRPCS.

scholarly journals Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

2020 ◽  
Vol 12 (5) ◽  
pp. 1967 ◽  
Author(s):  
Ziqi Wang ◽  
Peihan Wen
Keyword(s):  
Customer Satisfaction ◽  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Cold Chain ◽  
Carbon Trading ◽  
Low Carbon ◽  
Routing Problem ◽  
Heterogeneous Fleet

Due to the rise of social and environmental concerns on global climate change, developing the low-carbon economy is a necessary strategic step to respond to greenhouse effect and incorporate sustainability. As such, there is a new trend for the cold chain industry to establish the low-carbon vehicle routing optimization model which takes costs and carbon emissions as the measurements of performance. This paper studies a low-carbon vehicle routing problem (LC-VRP) derived from a real cold chain logistics network with several practical constraints, which also takes customer satisfaction into account. A low-carbon two-echelon heterogeneous-fleet vehicle routing problem (LC-2EHVRP) model for cold chain third-party logistics servers (3PL) with mixed time window under a carbon trading policy is constructed in this paper and aims at minimizing costs, carbon emissions and maximizing total customer satisfaction simultaneously. To find the optimal solution of such a nondeterministic polynomial (NP) hard problem, we proposed an adaptive genetic algorithm (AGA) approach validated by a numerical benchmark test. Furthermore, a real cold chain case study is presented to demonstrate the influence of the mixed time window’s changing which affect customers’ final satisfaction and the carbon trading settings on LC-2EHVRP model. Experiment of LC-2EHVRP model without customer satisfaction consideration is also designed as a control group. Results show that customer satisfaction is a critical influencer for companies to plan multi-echelon vehicle routing strategy, and current modest carbon price and trading quota settings in China have only a minimal effect on emissions’ control. Several managerial suggestions are given to cold chain logistics enterprises, governments, and even consumers to help improve the development of cold chain logistics.

Sweep Algorithm and Mixed Integer Linear Program for Vehicle Routing Problem with Time Windows

2018 ◽  
Vol 17 (04) ◽  
pp. 505-513 ◽  
Author(s):  
H. Savitri ◽  
D. A. Kurniawati
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Heuristic Method ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Routing Problem ◽  
Sweep Algorithm ◽  
A Company

CV. Jogja Transport is a company that distribute cakes “Sari Roti” in Yogyakarta, Indonesia. It has responsibility to distribute the cakes for every customer during the customers’ time windows. The distribution problem of CV. Jogja Transport belongs to Vehicle Routing Problem with Time Window (VRPTW). This paper tries to solve the problem of CV. Jogja Transport by proposing “cluster first route second” algorithm of simple heuristic method. Then the algorithm is combined with sweep algorithm for clustering the customers and Mixed Integer Linear Programming (MILP) to select the best route so that it can minimize the distance of each cluster. The result indicate that implementation of sweep algorithm and MILP can reduce the distances and the fuel up to 10.95% and the travel distance up to 2.60%.

scholarly journals An Enhanced Approach for the Multiple Vehicle Routing Problem with Heterogeneous Vehicles and a Soft Time Window

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 650 ◽  
Author(s):  
He-Yau Kang ◽  
Amy Lee
Keyword(s):  
Computer Science ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Computational Time ◽  
Routing Problem ◽  
Mip Model ◽  
Science Theory

The vehicle routing problem (VRP) is a challenging combinatorial optimization problem. This research focuses on the problem under which a manufacturer needs to outsource materials from other suppliers and to ship the materials back to the company. Heterogeneous vehicles are available to ship the materials, and each vehicle has a limited loading capacity and a limited travelling distance. The purpose of this research is to study a multiple vehicle routing problem (MVRP) with soft time window and heterogeneous vehicles. Two models, using mixed integer programming (MIP) and genetic algorithm (GA), are developed to solve the problem. The MIP model is first constructed to minimize the total transportation cost, which includes the assignment cost, travelling cost, and the tardiness cost, for the manufacturer. The optimal solution can present multiple vehicle routing and the loading size of each vehicle in each period. The GA is next applied to solve the problem so that a near-optimal solution can be obtained when the problem is too difficult to be solved using the MIP. A case of a food manufacturing company is used to examine the practicality of the proposed MIP model and the GA model. The results show that the MIP model can obtain the optimal solution under a short computational time when the scale of the problem is small. When the problem becomes non-deterministic polynomial hard (NP-hard), the MIP model cannot find the optimal solution. On the other hand, the GA model can obtain a near-optimal solution within a reasonable amount of computational time. This paper is related to several important topics of the Symmetry journal in the areas of mathematics and computer science theory and methods. In the area of mathematics, the theories of linear and non-linear algebraic structures and information technology are adopted. In the area of computer science, theory and methods, and metaheuristics are applied.

A Bi-Objective Vehicle Routing Problem with Time Window by Considering Customer Satisfaction

2016 ◽  
Vol 7 (2) ◽  
pp. 16-39 ◽  
Author(s):  
Masoud Rabbani ◽  
Mahyar Taheri ◽  
Mohammad Ravanbakhsh
Keyword(s):  
Customer Satisfaction ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Minimum Distance ◽  
Time Window ◽  
Time Windows ◽  
Time Frame ◽  
Capacity Constraint ◽  
Routing Problem ◽  
Bender's Decomposition

The Vehicle Routing Problem (VRP) by considering Time Windows is an essential and a reality optimization problem consisting in the determination of the set of routes with minimum distance to carry goods, by using some vehicles with capacity constraint; vehicles must visit customers within a time frame. In the recent years, many numbers of algorithm have been considered to solve a single objective formulate of VRPTW problem, such as Meta-heuristic, bender's decomposition, column generation and so on. This paper considers not only the minimum distance and the number of vehicles used to carry goods for customers. The customer satisfaction by considering the priority of the customers is considered which leads to service the customer as soon as possible. In this paper, the MOPSO and NSGAII approaches applied to solve the problem and then the authors compare the results of them; finally, they analysis the sensitivity of the capacity constraint for the vehicles

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.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

scholarly journals The last-mile vehicle routing problem with delivery options

OR Spectrum ◽  
2021 ◽  
Author(s):  
Christian Tilk ◽  
Katharina Olkis ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Resource Constraints ◽  
Time Window ◽  
Time Windows ◽  
Service Level ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Common Location ◽  
Delivery Options

AbstractThe ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers’ delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers’ overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations.

An evolutionary algorithm for the vehicle routing problem with route balancing

2009 ◽  
Vol 195 (3) ◽  
pp. 761-769 ◽  
Author(s):  
Nicolas Jozefowiez ◽  
Frédéric Semet ◽  
El-Ghazali Talbi
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Routing Problem
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