Study on Multi-Vehicle Refrigerated Distribution of Agricultural Products with Soft Time Windows

2013 ◽  
Vol 438-439 ◽  
pp. 2002-2005
Author(s):  
Feng Xu Li ◽  
Yue Fang Yang ◽  
Fei Wei ◽  
Feng Wei
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Time Windows ◽  
Agricultural Products ◽  
Route Optimization ◽  
Travel Costs ◽  
Soft Time Windows ◽  
Multiple Type

To the distribution status of agricultural products, this paper proposes a multiple-type vehicles refrigerated distribution route optimization model with soft time windows, innovatively considering that different type vehicles have different marginal and travel costs, and applies genetic algorithm to solve it. Finally, this paper uses an example to check the model, and proves that the model is feasible and effective.

Research on the Distribution Route Optimization of Agricultural Product Logistics Based on Particle Swarm

2013 ◽  
Vol 790 ◽  
pp. 690-696
Author(s):  
Jun Liu ◽  
Jun Xiang ◽  
Gui Lan Zou
Keyword(s):  
Optimization Model ◽  
Time Windows ◽  
Particle Swarm ◽  
Agricultural Products ◽  
Route Optimization ◽  
Agricultural Product ◽  
Swarm Optimization ◽  
Logistics Distribution ◽  
Optimum Model ◽  
The Cost

Through an analysis of the characteristics of the Agricultural Products Logistics and its influence on the vehicle scheduling, this paper is to describe the vehicle routes whose vehicle number is uncertain and which are with time windows, to establish a distribution route optimization model which is effected by the cost and has a time limitation, to solve the model with the Compound Optimum Model Particle Swarm Optimization, and to compare it through some case. The optimization model of Agricultural Products Logistics has good practical value on reduce the cost of agricultural products logistics and improve the efficiency of logistics distribution of agricultural products.

scholarly journals A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Chenghua Shi ◽  
Tonglei Li ◽  
Yu Bai ◽  
Fei Zhao
Keyword(s):  
Genetic Algorithm ◽  
Time Windows ◽  
Computation Time ◽  
Routing Problem ◽  
Split Delivery ◽  
Soft Time Windows ◽  
Comparison Results ◽  
Potential Demand ◽  
The Cost

We present the vehicle routing problem with potential demands and time windows (VRP-PDTW), which is a variation of the classical VRP. A homogenous fleet of vehicles originated in a central depot serves customers with soft time windows and deliveries from/to their locations, and split delivery is considered. Also, besides the initial demand in the order contract, the potential demand caused by conformity consuming behavior is also integrated and modeled in our problem. The objective of minimizing the cost traveled by the vehicles and penalized cost due to violating time windows is then constructed. We propose a heuristics-based parthenogenetic algorithm (HPGA) for successfully solving optimal solutions to the problem, in which heuristics is introduced to generate the initial solution. Computational experiments are reported for instances and the proposed algorithm is compared with genetic algorithm (GA) and heuristics-based genetic algorithm (HGA) from the literature. The comparison results show that our algorithm is quite competitive by considering the quality of solutions and computation time.

scholarly journals TDGVRPSTW of Fresh Agricultural Products Distribution: Considering Both Economic Cost and Environmental Cost

2021 ◽  
Vol 11 (22) ◽  
pp. 10579
Author(s):  
Daqing Wu ◽  
Chenxiang Wu
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Economic Cost ◽  
Agricultural Products ◽  
Time Dependent ◽  
Environmental Cost ◽  
Routing Problem ◽  
Measure Function

The time-dependent vehicle routing problem of time windows of fresh agricultural products distribution have been studied by considering both economic cost and environmental cost. A calculation method for road travel time across time periods is designed in this study. A freshness measure function of agricultural products and a measure function of carbon emission rate are employed by considering time-varying vehicle speeds, fuel consumptions, carbon emissions, perishable agricultural products, customers’ time windows, and minimum freshness. A time-dependent green vehicle routing problem with soft time windows (TDGVRPSTW) model is formulated. The object of the TDGVRPSTW model is to minimize the sum of economic cost and environmental cost. According to the characteristics of the model, a new variable neighborhood adaptive genetic algorithm is designed, which integrates the global search ability of the genetic algorithm and the local search ability of the variable neighborhood descent algorithm. Finally, the experimental data show that the proposed approaches effectively avoid traffic congestions, reduce total distribution costs, and promote energy conservation and emission reduction.

Research on the Route Optimization as to Timing Uncertainty of Wartime Transportation

2014 ◽  
Vol 556-562 ◽  
pp. 5328-5332
Author(s):  
Lin Zhu ◽  
Xiao Dun ◽  
Can Shi Zhu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Traditional Method ◽  
Uncertain Parameter ◽  
Route Optimization ◽  
Objective Functions ◽  
Improved Genetic Algorithm ◽  
Routing Optimization ◽  
Timing Uncertainty ◽  
Pass Through

Affected with various factors in wartime, the time during which the transport vehicles of military supplies pass through a certain section of a route is an uncertain parameter, whose optimization objective functions and constraints cannot be defined and solved through the traditional method of deterministic planning. In response to the problem, a routing optimization model is put forward herein for the timing uncertainty of wartime transportation and a method is devised for the Improved Genetic Algorithm to solve the routing optimization model with respect to timing uncertainty. Examples are also cited to verify the rationality of the algorithm as well as the correctness of the model.

scholarly journals Two-Echelon Location-Routing Problem with Time Windows and Transportation Resource Sharing

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yong Wang ◽  
Yaoyao Sun ◽  
Xiangyang Guan ◽  
Yanyong Guo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Resource Sharing ◽  
Hybrid Algorithm ◽  
Time Windows ◽  
Operating Cost ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Logistics Networks ◽  
Location Routing

In this work, a two-echelon location-routing problem with time windows and transportation resource sharing (2E-LRPTWTRS) is solved by selecting facility locations and optimizing two-echelon vehicle routes. The optimal solutions improve the efficiency of a logistics network based on the geographical distribution and service time windows of logistics facilities and customers. Furthermore, resource utilization is maximized by enabling resource sharing strategies within and among different logistics facilities simultaneously. The 2E-LRPTWTRS is formulated as a biobjective optimization model, and obtaining the smallest number of required delivery vehicles and the minimum total operating cost are the two objective functions. A two-stage hybrid algorithm composed of k-means clustering and extended multiobjective particle swarm optimization algorithm is proposed for 2E-LRPTWTRS optimization. A self-adaptive mechanism of flight parameters is introduced and adopted during the iterative process to balance the evolution of particles and improve the efficiency of the two-stage hybrid algorithm. Moreover, 20 small-scale instances are used for an algorithm comparison with multiobjective genetic algorithm and nondominated sorting genetic algorithm-II, and the solutions demonstrate the superiority of the proposed algorithm in optimizing logistics networks. The proposed optimization model and hybrid algorithm are tested by employing a real-world case of 2E-LRPTWTRS in Chongqing, China, and the optimization results verify the positive role of the developed model and algorithm in improving logistics efficiency, reducing operating cost, and saving transportation resources in the operations of two-echelon logistics networks.

scholarly journals Vehicle Routing Problem with Soft Time Windows Based on Improved Genetic Algorithm for Fruits and Vegetables Distribution

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Peiqing Li ◽  
Jie He ◽  
Dunyong Zheng ◽  
Yongsheng Huang ◽  
Chenhao Fan
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Fruits And Vegetables ◽  
Time Windows ◽  
Improved Genetic Algorithm ◽  
Routing Problem ◽  
Total Cost ◽  
Soft Time Windows ◽  
Distribution Process

Fresh fruits and vegetables, perishable by nature, are subject to additional deterioration and bruising in the distribution process due to vibration and shock caused by road irregularities. A nonlinear mathematical model was developed that considered not only the vehicle routing problem with time windows but also the effect of road irregularities on the bruising of fresh fruits and vegetables. The main objective of this work was to obtain the optimal distribution routes for fresh fruits and vegetables considering different road classes with the least amount of logistics costs. An improved genetic algorithm was used to solve the problem. A fruit delivery route among the 13 cities in Jiangsu Province was used as a real analysis case. The simulation results showed that the vehicle routing problem with time windows, considering road irregularities and different classes of toll roads, can significantly influence total delivery costs compared with traditional VRP models. The comparison between four models to predict the total cost and actual total cost in distribution showed that the improved genetic algorithm is superior to the Group-based pattern, CW pattern, and O-X type cross pattern.

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