A Route Optimizing Model and Algorithm for Pickup and Delivery Problem with Time Window

2013 ◽  
Vol 321-324 ◽  
pp. 2060-2064
Author(s):  
Ting Ting Wu
Keyword(s):  
Optimization Problems ◽  
Time Window ◽  
Time Windows ◽  
Minimum Cost ◽  
Pickup And Delivery ◽  
Delivery Problem ◽  
Soft Time Windows ◽  
Routing Optimization ◽  
Optimizing Model ◽  
Vehicle Routing Optimization

Choosing in the more practical soft time Windows the logistics pickup and delivery path choice is discussed. Setting up a more comprehensive model to get the minimum cost including the distance and time. Then improving the genetic algorithm to solve the vehicle routing optimization problems better.

scholarly journals On the Use of Learnheuristics in Vehicle Routing Optimization Problems with Dynamic Inputs

Algorithms ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 208 ◽  
Author(s):  
Quim Arnau ◽  
Angel Juan ◽  
Isabel Serra
Keyword(s):  
Vehicle Routing ◽  
Optimization Problems ◽  
Time Windows ◽  
Real Life ◽  
Routing Problem ◽  
Routing Optimization ◽  
Statistical Learning Techniques ◽  
Critical Activity ◽  
The Cost ◽  
Vehicle Routing Optimization

Freight transportation is becoming an increasingly critical activity for enterprises in a global world. Moreover, the distribution activities have a non-negligible impact on the environment, as well as on the citizens’ welfare. The classical vehicle routing problem (VRP) aims at designing routes that minimize the cost of serving customers using a given set of capacitated vehicles. Some VRP variants consider traveling times, either in the objective function (e.g., including the goal of minimizing total traveling time or designing balanced routes) or as constraints (e.g., the setting of time windows or a maximum time per route). Typically, the traveling time between two customers or between one customer and the depot is assumed to be both known in advance and static. However, in real life, there are plenty of factors (predictable or not) that may affect these traveling times, e.g., traffic jams, accidents, road works, or even the weather. In this work, we analyze the VRP with dynamic traveling times. Our work assumes not only that these inputs are dynamic in nature, but also that they are a function of the structure of the emerging routing plan. In other words, these traveling times need to be dynamically re-evaluated as the solution is being constructed. In order to solve this dynamic optimization problem, a learnheuristic-based approach is proposed. Our approach integrates statistical learning techniques within a metaheuristic framework. A number of computational experiments are carried out in order to illustrate our approach and discuss its effectiveness.

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

The pickup and delivery problem with time windows

1991 ◽  
Vol 54 (1) ◽  
pp. 7-22 ◽  
Author(s):  
Yvan Dumas ◽  
Jacques Desrosiers ◽  
François Soumis
Keyword(s):  
Time Windows ◽  
Pickup And Delivery ◽  
Delivery Problem ◽  
Pickup And Delivery Problem

The pickup and delivery problem with time windows and occasional drivers

2019 ◽  
Vol 109 ◽  
pp. 122-133 ◽  
Author(s):  
Lars Dahle ◽  
Henrik Andersson ◽  
Marielle Christiansen ◽  
M. Grazia Speranza
Keyword(s):  
Time Windows ◽  
Pickup And Delivery ◽  
Delivery Problem ◽  
Pickup And Delivery Problem
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