scholarly journals Optimization of Port Emergency Materials Dispatch with Time Windows Constraints under Uncertainties

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Bowei Xu ◽  
Yuqing Wang ◽  
Junjun Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Time Window ◽  
Time Windows ◽  
Bilevel Optimization ◽  
Container Terminals ◽  
Adaptive Genetic Algorithm ◽  
Short Term ◽  
Total Cost ◽  
Logistic Mapping

Uncertainties exist and affect the actual port production. For example, at the beginning of 2020, the sudden outbreak of COVID-19 seriously affected terminal production and increased the short-term pressure of handling at container terminals. Consequently, a large number of containers were stacked at terminals, and the problem of terminal congestion became more serious. To solve the congestion problem of container terminals and ensure the priority dispatch of emergency materials, this study uses the optimized arrival patterns of external trucks and a priority dispatch strategy for emergency materials to establish a bilevel optimization model for container terminals and proposes a chaotic genetic algorithm based on logistic mapping as a solution. Through numerical experiments, the algorithm proposed in this study was compared with the genetic algorithm and adaptive genetic algorithm. The experimental results show that the model and algorithm proposed in this study can effectively reduce the total cost of containers in a terminal while ensuring the priority dispatch of emergency materials, reducing the overlapping part of the time window, optimizing the arrival mode of external trucks, and reducing the waiting time of external trucks, effectively alleviating the terminal congestion problem.

scholarly journals Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 724
Author(s):  
Yiping Jiang ◽  
Bei Bian ◽  
Lingling Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Postharvest Quality ◽  
Online Retailing ◽  
Quality Deterioration ◽  
Distribution Scheduling ◽  
Proposed Model

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

scholarly journals Integrated Tomato Picking and Distribution Scheduling Based on Maturity

2020 ◽  
Vol 12 (19) ◽  
pp. 7934
Author(s):  
Anqi Zhu ◽  
Bei Bian ◽  
Yiping Jiang ◽  
Jiaxiang Hu
Keyword(s):  
Genetic Algorithm ◽  
Time Windows ◽  
Joint Optimization ◽  
Adaptive Genetic Algorithm ◽  
Maturity Model ◽  
Improved Genetic Algorithm ◽  
Routing Problem ◽  
Order Processing ◽  
Supply Chain Efficiency ◽  
Distribution Scheduling

Agriproducts have the characteristics of short lifespan and quality decay due to the maturity factor. With the development of e-commerce, high timelines and quality have become a new pursuit for agriproduct online retailing. To satisfy the new demands of customers, reducing the time from receiving orders to distribution and improving agriproduct quality are significantly needed advancements. In this study, we focus on the joint optimization of the fulfillment of online tomato orders that integrates picking and distribution simultaneously within the context of the farm-to-door model. A tomato maturity model with a firmness indicator is proposed firstly. Then, we incorporate the tomato maturity model function into the integrated picking and distribution schedule and formulate a multiple-vehicle routing problem with time windows. Next, to solve the model, an improved genetic algorithm (the sweep-adaptive genetic algorithm, S-AGA) is addressed. Finally, we prove the validity of the proposed model and the superiority of S-AGA with different numerical experiments. The results show that significant improvements are obtained in the overall tomato supply chain efficiency and quality. For instance, tomato quality and customer satisfaction increased by 5% when considering the joint optimization, and the order processing speed increased over 90% compared with traditional GA. This study could provide scientific tomato picking and distribution scheduling to satisfy the multiple requirements of consumers and improve agricultural and logistics sustainability.

scholarly journals Research on Logistics Distribution Path Planning Based on Genetic Algorithm

2021 ◽  
Vol 2083 (3) ◽  
pp. 032013
Author(s):  
Shaokun Liu
Keyword(s):  
Genetic Algorithm ◽  
Simulation Experiment ◽  
Time Window ◽  
Planning Model ◽  
Genetic Operators ◽  
Intelligent Algorithm ◽  
Total Cost ◽  
Logistics Distribution ◽  
Survey Results ◽  
Distribution Cost

Abstract In this paper, SF express company Jinzhou Guta District Pinganli business point as an example, to investigate its distribution, statistical analysis of the survey results, summed up the problems in logistics and distribution. Through the systematic study of the problem, a planning model with time window and with the objective of minimizing the total cost of distribution is established. At the same time, an intelligent algorithm for distribution path optimization - Genetic Algorithm (GA) is designed. Genetic algorithm is used to design chromosome coding methods and genetic operators for solving the planning model with the objective of minimizing the total cost of distribution. Finally, the simulation experiment is carried out. MATLAB software is used to solve the distribution route and the total driving distance of vehicles, and the distribution route with the goal of minimizing the total distribution cost is obtained.

Scheduling of Yard Truck Considering Loading and Unloading Simultaneously in an Underground Container Logistics System

2021 ◽  
pp. 036119812110478
Author(s):  
Yinping Gao ◽  
Daofang Chang ◽  
Jun Yuan ◽  
Chengji Liang
Keyword(s):  
Genetic Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Operating Efficiency ◽  
Adaptive Genetic Algorithm ◽  
Integer Programming Problem ◽  
Logistics System ◽  
Container Logistics ◽  
Loading And Unloading ◽  
Mixed Integer Programming Problem

With the rapid growth of containers and scarce of land, the underground container logistics system (UCLS) presents a logical alternative for container terminals to better protect the environment and relieve traffic pressure. The operating efficiency of container terminals is one of the competitive edges over other terminals, which requires UCLS to be well integrated with the handling process of the storage yard. In UCLS, yard trucks (YTs) serve different handling points dynamically instead of one fixed handling point, and yard cranes (YCs) perform loading and unloading simultaneously. To minimize the total time of handling all containers in UCLS, the mixed integer programming problem is described and solved using an adaptive genetic algorithm (AGA). The convergence speed and accuracy of AGA are demonstrated by comparison with conventional genetic algorithm (GA). Additionally, AGA and CPLEX are compared with different scale cases. Experimental results show that the proposed algorithm is superior to CPLEX in resulted solutions and calculation time. A sensitivity analysis is provided to obtain reasonable numbers of YTs for scheduling between handling points and the storage yard in UCLS.

scholarly journals Allocating Freight Empty Cars in Railway Networks with Dynamic Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ce Zhao ◽  
Lixing Yang ◽  
Shukai Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Transportation Cost ◽  
Allocation Problem ◽  
Total Cost ◽  
Storage Cost ◽  
Proposed Model ◽  
Railway Networks

This paper investigates the freight empty cars allocation problem in railway networks with dynamic demands, in which the storage cost, unit transportation cost, and demand in each stage are taken into consideration. Under the constraints of capacity and demand, a stage-based optimization model for allocating freight empty cars in railway networks is formulated. The objective of this model is to minimize the total cost incurred by transferring and storing empty cars in different stages. Moreover, a genetic algorithm is designed to obtain the optimal empty cars distribution strategies in railway networks. Finally, numerical experiments are given to show the effectiveness of the proposed model and algorithm.

scholarly journals A Hybrid Multi-objective Genetic Algorithm for Bi-objective Time Window Assignment Vehicle Routing Problem

2019 ◽  
Vol 31 (5) ◽  
pp. 513-525
Author(s):  
Manman Li ◽  
Jian Lu ◽  
Wenxin Ma
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Routing Problem ◽  
Multi Objective ◽  
Objective Time ◽  
Multi Objective Genetic Algorithm ◽  
Positive Effect

Providing a satisfying delivery service is an important way to maintain the customers’ loyalty and further expand profits for manufacturers and logistics providers. Considering customers’ preferences for time windows, a bi-objective time window assignment vehicle routing problem has been introduced to maximize the total customers’ satisfaction level for assigned time windows and minimize the expected delivery cost. The paper designs a hybrid multi-objective genetic algorithm for the problem that incorporates modified stochastic nearest neighbour and insertion-based local search. Computational results show the positive effect of the hybridization and satisfactory performance of the metaheuristics. Moreover, the impacts of three characteristics are analysed including customer distribution, the number of preferred time windows per customer and customers’ preference type for time windows. Finally, one of its extended problems, the bi-objective time window assignment vehicle routing problem with time-dependent travel times has been primarily studied.

A Fuzzy Measure of Vulnerability for the Optimization of Vehicle Routing Problems With Time Windows

2018 ◽  
pp. 167-197
Author(s):  
Kris Braekers ◽  
Gerrit K. Janssens
Keyword(s):  
Vehicle Routing ◽  
Time Window ◽  
Time Windows ◽  
Fuzzy Measure ◽  
Travel Distance ◽  
Service Needs ◽  
Routing Problem ◽  
Total Cost ◽  
Cost Criterion ◽  
Service Agreement

In a vehicle routing problem (VRP) with time windows, the start of service needs to take place within the customer time window. Due to uncertainty on travel times, vehicles might arrive late at a customer's site. A VRP is mostly solved to minimize a total cost criterion (travel time, travel distance, fixed and variable vehicle costs). But the dispatcher might also take into consideration the risk of non-conformance with the service agreement to start service within the time window. Therefore, a measure of risk, called “vulnerability of a solution,” is developed to serve as a second criterion. This chapter develops such a measure based on a distance metric and investigates its strengths and weaknesses.

scholarly journals A new scheduling method based on sequential time windows developed to distribute first-aid medicine for emergency logistics following an earthquake

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247566
Author(s):  
Jiaqi Fang ◽  
Hanping Hou ◽  
Changxiang Lu ◽  
Haiyun Pang ◽  
Qingshan Deng ◽  
...  
Keyword(s):  
Demand Uncertainty ◽  
Time Window ◽  
Supply And Demand ◽  
Time Windows ◽  
First Aid ◽  
Short Term ◽  
Emergency Logistics ◽  
Scheduling Method ◽  
Scheduling Models

After an earthquake, affected areas have insufficient medicinal supplies, thereby necessitating substantial distribution of first-aid medicine from other supply centers. To make a proper distribution schedule, we considered the timing of supply and demand. In the present study, a “sequential time window” is used to describe the time to generate of supply and demand and the time of supply delivery. Then, considering the sequential time window, we proposed two multiobjective scheduling models with the consideration of demand uncertainty; two multiobjective stochastic programming models were also proposed to solve the scheduling models. Moreover, this paper describes a simulation that was performed based on a first-aid medicine distribution problem during a Wenchuan earthquake response. The simulation results show that the methodologies proposed in this paper provide effective schedules for the distribution of first-aid medicine. The developed distribution schedule enables some supplies in the former time windows to be used in latter time windows. This schedule increases the utility of limited stocks and avoids the risk that all the supplies are used in the short-term, leaving no supplies for long-term use.

The Research on the Optimization of Transportation Routing for Fresh Food by Improved Genetic Algorithm

2012 ◽  
Vol 178-181 ◽  
pp. 1790-1796 ◽  
Author(s):  
Ying Wu ◽  
Zi Bo Meng ◽  
Min Peng
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Customer Satisfaction ◽  
Time Window ◽  
Time Windows ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Transport Services ◽  
Fresh Food ◽  
Transportation Routing

In this paper, we research the problem of transportation routing for fresh food. We analyzed the limit of soft and hard time windows in transportation and formed the time window with fuzzy appointment based on customer satisfaction. The optimization of transportation routes mathematical model was structured. The improved genetic algorithm has been applied to matlab progam. This progam has found the optimal solution in the model. We used a case to prove the feasibility of the model and the algorithm. It has twelve customers and one DC need to transport services. The mathematical model is to simulate the transport of fresh food within realistic.The transportation routing is designed to improve customer satisfaction and reduce transportation costs.

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