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Solving vehicle routing problem with time windows using metaheuristic approaches

International Journal of Intelligent Computing and Cybernetics 2023年第1期16卷 121-138页

作者： Zeynep Aydınalp DoganÖzgen Yıldız Technical University IstanbulTurkey

Purpose-Drugs are strategic products with essential functions in human health.An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health.The vehicle-routing problem,focused on finding the lowest-cost routes with available vehicles and constraints,such as time constraints and road length,is an important aspect of this.In this paper,the vehicle routing problem(VRP)for a pharmaceutical company in Turkey is discussed.Design/methodology/approach-A mixed-integer programming(MIP)model based on the vehicle routing problem with time windows(VRPTW)is presented,aiming to minimize the total route cost with certain constraints.As the model provides an optimum solution for small problem sizes with the GUROBI®solver,for large problem sizes,metaheuristic methods that simulate annealing and adaptive large neighborhood search algorithms are proposed.A real dataset was used to analyze the effectiveness of the metaheuristic algorithms.The proposed simulated annealing(SA)and adaptive large neighborhood search(ALNS)were evaluated and compared against GUROBI®and each other through a set of real problem instances.Findings-The model is solved optimally for a small-sized dataset with exact algorithms;for solving a larger dataset,however,metaheuristic algorithms require significantly lesser time.For the problem addressed in this study,while the metaheuristic algorithms obtained the optimum solution in less than one minute,the solution in the GUROBI®solver was limited to one hour and three hours,and no solution could be obtained in this time interval.Originality/value-The VRPTW problem presented in this paper is a real-life problem.The vehicle fleet owned by the factory cannot be transported between certain suppliers,which complicates the solution of the problem.

关键词： Pharmaceutical supply chain Network design Mixed-integer linear programming vehicle routing problem Simulated annealing Adaptive large neighborhood search

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Genetic Crossover Operators for the Capacitated vehicle routing problem

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Computers, Materials & Continua 2023年第1期74卷 1575-1605页

作者： Zakir Hussain Ahmed Naif Al-Otaibi Abdullah Al-Tameem Abdul Khader Jilani Saudagar Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia

We study the capacitated vehicle routing problem(CVRP)which is a well-known NP-hard combinatorial optimization problem(COP).The aim of the problem is to serve different customers by a convoy of vehicles starting from a depot so that sum of the routing costs under their capacity constraints is minimized.Since the problem is very complicated,solving the problem using exact methods is almost impossible.So,one has to go for the heuristic/metaheuristic methods and genetic algorithm(GA)is broadly applied metaheuristic method to obtain near optimal solution to such COPs.So,this paper studies GAs to find solution to the problem.Generally,to solve a COP,GAs start with a chromosome set named initial population,and then mainly three operators-selection,crossover andmutation,are applied.Among these three operators,crossover is very crucial in designing and implementing GAs,and hence,numerous crossover operators were developed and applied to different COPs.There are two major kinds of crossover operators-blind crossovers and distance-based crossovers.We intend to compare the performance of four blind crossover and four distance-based crossover operators to test the suitability of the operators to solve the CVRP.These operators were originally proposed for the standard travelling salesman problem(TSP).First,these eight crossovers are illustrated using same parent chromosomes for building offspring(s).Then eight GAs using these eight crossover operators without any mutation operator and another eight GAs using these eight crossover operators with a mutation operator are developed.These GAs are experimented on some benchmark asymmetric and symmetric instances of numerous sizes and various number of vehicles.Our study revealed that the distance-based crossovers are much superior to the blind crossovers.Further,we observed that the sequential constructive crossover with and without mutation operator is the best one for theCVRP.This estimation is validated by Student’s t-test at 95%confidence level.We further determined a comparati

关键词： vehicle routing problem NP-hard genetic algorithm sequential constructive crossover mutation

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A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon vehicle routing problem

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Complex System Modeling and Simulation 2022年第2期2卷 142-155页

作者： Xiaoning Shen Jiaqi Lu Xuan You Liyan Song Zhongpei Ge Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Trustworthy Autonomous Systems and also with the Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent ComputationDepartment of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

A constrained multi-objective optimization model for the low-carbon vehicle routing problem(VRP)is established.A carbon emission measurement method considering various practical factors is introduced.It minimizes both the total carbon emissions and the longest time consumed by the sub-tours,subject to the limited number of available vehicles.According to the characteristics of the model,a region enhanced discrete multi-objective fireworks algorithm is proposed.A partial mapping explosion operator,a hybrid mutation for adjusting the sub-tours,and an objective-driven extending search are designed,which aim to improve the convergence,diversity,and spread of the non-dominated solutions produced by the algorithm,respectively.Nine low-carbon VRP instances with different scales are used to verify the effectiveness of the new strategies.Furthermore,comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon VRP.It provides a promising scalability to the problem size.

关键词： vehicle routing problem carbon emission multi-objective optimization fireworks algorithm region enhanced

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vehicle routing problem with time-varying speed

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Journal of Harbin Institute of Technology(New Series) 2010年第4期17卷 584-587页

作者：刘云忠 Statistic School Xi’an University of Finance and Economics

vehicle routing problem with time-varying speed ( VRPTS) is a generalization of vehicle routing problem in which the travel speed between two locations depends on the passing areas and the time of a day. This paper proposes a simple model for estimating time-varying travel speeds in VRPTS that relieves much burden to the data-related problems. The study further presents three heuristics ( saving technique,proximity priority searching technique,and insertion technique) for VRPTS,developed by extending and modifying the existing heuristics for conventional VRP. The results of computational experiments demonstrate that the proposed estimation model performs well and the saving technique is the best among the three heuristics.

关键词： vehicle routing problem time-varying speed saving technique proximity priority searching technique insertion technique

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Full truckload vehicle routing problem with profits

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Journal of Traffic and Transportation Engineering(English Edition) 2014年第2期1卷 146-152页

作者： Jian Li Wenhua Lu College of Engineering Nanjing Agricultural University

A new variant of the full truckload vehicle routing problem is studied. In this problem there are more than one delivery points corresponding to the same pickup point, and one order is allowed to be served several times by the same vehicle or different vehicles. For the orders which cannot be assigned because of resource constraint, the logistics company outsources them to other logistics companies at a certain cost. To maximize its profits, logistics company decides which to be transported by private fleet and which to be outsourced. The mathematical model is constructed for the problem. Since the problem is NP-hard and it is difficult to solve the large-scale problems with an exact algorithm, a hybrid genetic algorithm is proposed. Computational results show the effectiveness of the hybrid genetic algorithm.

关键词： full truckload vehicle routing problem genetic algorithm profit

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vehicle routing problem WITH TRAVEL TIME RELIABILITY CONSTRAIN

VEHICLE ROUTING PROBLEM WITH TRAVEL TIME RELIABILITY CONSTRA...

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第一届交通运输工程国际学术会议

作者： TANG Lian-sheng1, CHENG Wen-ming1, ZHANG Ze-qiang1, and LIANG jian1 1Research Institute of Mechanical Engineering, Southwest Jiaotong University, Erhuanlu Beiyiduan, Chengdu, No.111

Considered the road network traffic flow stochastic change, the road network reliable theory is introduced to the vehicles routing problem and the concept of vehicle routing problem with travel time reliability （VRPTTR） is proposed. The change rule based on the travel time has been analyzed according to the state of roads. Also we put forward a solution of VRPTTR. The ant colony algorithm is introduced to resolve VRPTTR. The method has been proven to be effective from a case.

关键词： Travel time Reliability Ant colony algorithm vehicle routing problem

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Intelligent Iterated Local Search Methods for Solving vehicle routing problem with Different Fleets

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Journal of Southwest Jiaotong University(English Edition) 2007年第4期15卷 344-352页

作者：李妍峰李军赵达 School of Economics and Management Southwest Jiaotong University Caotang School Sichuan Normal University Chengdu 610072 China

To solve vehicle routing problem with different fleets, two methodologies are developed. The first methodology adopts twophase strategy. In the first phase, the improved savings method is used to assign customers to appropriate vehicles. In the second phase, the iterated dynasearch algorithm is adopted to route each selected vehicle with the assigned customers. The iterated dynasearch algorithm combines dynasearch algorithm with iterated local search algorithm based on random kicks. The second methodplogy adopts the idea of cyclic transfer which is performed by using dynamic programming algorithm, and the iterated dynasearch algorithm is also embedded in it. The test results show that both methodologies generate better solutions than the traditional method, and the second methodology is superior to the first one.

关键词： vehicle routing problem Savings method Iterated dynasearch algorithm Dynamic programming Iterated local search Random kick Cyclic transfer

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A Hybrid Genetic Algorithm for vehicle routing problem with Complex Constraints

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International Journal of Plant Engineering and Management 2006年第2期11卷 88-96页

作者： CHEN Yan LU Jun LI Zeng-zhi School of Electronics and Information Engineering Xi＇an Jiaotong University Xi＇an 710049 P. R. China

Most research on the vehicle routing problem （VRP） is focused on standard conditions, which is not suitable for specific cases. A Hybrid Genetic Algorithm is proposed to solve a vehicle routing problem （VRP） with complex side constraints. A novel coding method is designed especially for side constraints. A greedy algorithm combined with a random algorithm is introduced to enable the diversity of the initial population, as well as a local optimization algorithm employed to improve the searching efficiency. In order to evaluate the performance, this mechanism has been implemented in an oil distribution center, the experimental and executing results show that the near global optimal solution can be easily and quickly obtained by this method, and the solution is definitely satisfactory in the VRP application.

关键词： genetic algorithm vehicle routing problem greedy algorithm complex constraints

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Application of Ant Colony Algorithm in Emergency Logistics vehicle routing problem

Application of Ant Colony Algorithm in Emergency Logistics V...

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2010 International Conference on Services Science, Management and Engineering (SSME 2010)

作者： Yanqin LI Chunsheng GUO Department of Disaster Prevention Equipment Institute of Disaster Prevention Science and Technology Hebei China Liyi ZHANG Yunshan SUN Department of Information Engineering Tianjin University of Commerce Tianjin China

Ant colony algorithm is a kind of new simulation-biological evolution algorithm.An ant colony algorithm was utilized to solve the vehicle routing problem in emergency logistics.Restraint factors of emergency logistics were studied in the paper,and math model of emergency logistics vehicle routing problem was constructed.The algorithm was simulated by MATLAB.The experimental results show that the ant colony algorithm possesses better optimization effect than the traditional genetic algorithm.The algorithm possesses theory value and practical meaning.

关键词： emergency logistics ant colony algorithm vehicle routing problem routing optimization

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MULTI-GENERATION COMPETE GENETIC ALGORITHMS AND ITS APPLICATION IN vehicle routing problem

MULTI-GENERATION COMPETE GENETIC ALGORITHMS AND ITS APPLICAT...

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第一届交通运输工程国际学术会议

作者： DENG Lianbo SHI Feng and LIANG Ting Traffic and Transportation Engineering School Central South University ChangSha 410075

Age and life-span was imported to genetic algorithm for overcoming the low efficiency, when the algorithm is used to vehicle routing problem. Multi-generation Compete Genetic Algorithm is put forward. At each iteration some individuals are updated by descendible mode. Each individual, according to its age and life-span, is judged whether it is kept down to next generation population, or its life was terminated. By this means, survived generations of some better individuals were prolonged in the generation population and the probability of their propagation increased. Some better solutions are presented through using the algorithms.

关键词： vehicle routing problem Multi-generation Compete Genetic Algorithm

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