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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Industrial Engineering International
- نوع مقاله: Journal Article
- کلمات کلیدی: Simulated Annealing,vehicle routing problem,Stochastic travel times,Driver's satisfaction
- چکیده:
- چکیده انگلیسی: A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm.
- انتشار مقاله: 10-07-1399
- نویسندگان: Reza Tavakkoli-Moghaddam,Mehdi Alinaghian,Alireza Salamat-Bakhsh,Narges Norouzi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Green vehicle routing problem,Fuel consumption,Improved particle swarm optimization
- چکیده:
- چکیده انگلیسی: In recent years, reducing emissions has become an important issue. Besides reducing the economic costs, reducing the fuel consumption decreases emissions, pollutant impact and increases society health as well. Green vehicle routing problem are a major key to reduce hazardous effects of transportation such as air pollution, Greenhouse Gas (GHG) emissions, noise and the like. Generally, the amount of pollution emitted by a vehicle over an arc depends on many factors like vehicle load, travel speed, travel distance, road slop and etc. Vehicle load has a major effect among other factors on amount of emissions and influences the route selection. Some works were completed on the estimation of the cost of the GHG emissions. Therefore, the effect of the carried load in fuel consumption is contributed in the model by minimizing a weighted load function. This paper presents a new method for vehicle routing problem with minimizing fuel consumption and number of vehicles. Distributing managers are often interested in minimizing fuel consumption caused by two reasons: 1) reducing fuel consumption caused to reduce the service cost, economic costs and increasing customer’s satisfaction, and 2) reducing fuel consumption is a way for reducing pollutant negative impact on our environment and increasing society health. Also, minimizing the number of vehicles is caused the reducing in fixed and other related cost. It is proven that VRPs belong to the category of NP-Hard problems thus due to the complexity of VRP with exact methods in large-scale problems, a meta-heuristic method based on particle swarm optimization is proposed, so called improved particle swarm optimization (IPSO). In addition, to show the efficiency of the proposed IPSO, a number of test problems in small and large sizes are proposed and solved by the IPSO. Then, the obtained results are evaluated with the results obtained by Lingo.
- انتشار مقاله: 10-04-1391
- نویسندگان: Narges Norouzi,Jafar Razmi,Mohsen Sadegh Amalnick
- مشاهده