An XGBoost-enhanced fast constructive algorithm for food delivery route planning problem

2021 ◽  
Vol 152 ◽  
pp. 107029
Author(s):  
Xing Wang ◽  
Ling Wang ◽  
Shengyao Wang ◽  
Jing-fang Chen ◽  
Chuge Wu
Keyword(s):  
Route Planning ◽  
Food Delivery ◽  
Planning Problem ◽  
Constructive Algorithm ◽  
Delivery Route

scholarly journals Solving two-stage stochastic route-planning problem in milliseconds via end-to-end deep learning

2021 ◽  
Author(s):  
Jie Zheng ◽  
Ling Wang ◽  
Shengyao Wang ◽  
Yile Liang ◽  
Jize Pan
Keyword(s):  
Deep Learning ◽  
Programming Model ◽  
Search Algorithm ◽  
Rapid Development ◽  
Optimization Technique ◽  
Route Planning ◽  
Food Delivery ◽  
Planning Problem ◽  
Two Stage ◽  
End To End

AbstractWith the rapid development of e-economy, ordering via online food delivery platforms has become prevalent in recent years. Nevertheless, the platforms are facing lots of challenges such as time-limitation and uncertainty. This paper addresses a complex stochastic online route-planning problem (SORPP) which is mathematically formulated as a two-stage stochastic programming model. To meet the immediacy requirement of online fashion, an end-to-end deep learning model is designed which is composed of an encoder and a decoder. To embed different problem-specific features, different network layers are adopted in the encoder; to extract the implicit relationship, the probability mass functions of stochastic food preparation time is processed by a convolution neural network layer; to provide global information, the location map and rider features are handled by the factorization-machine (FM) and deep FM layers, respectively; to screen out valuable information, the order features are embedded by attention layers. In the decoder, the permutation sequence is predicted by long-short term memory cells with attention and masking mechanism. To learn the policy for finding optimal permutation under complex constraints of the SORPP, the model is trained in a supervised learning way with the labels obtained by iterated greedy search algorithm. Extensive experiments are conducted based on real-world data sets. The comparative results show that the proposed model is more efficient than meta-heuristics and is able to yield higher quality solutions than heuristics. This work provides an intelligent optimization technique for complex online food delivery system.

Route planning of intelligent bridge cranes based on an improved artificial potential field method

2021 ◽  
pp. 1-8
Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li
Keyword(s):  
Potential Field ◽  
Autonomous Navigation ◽  
Route Planning ◽  
Simple Algorithm ◽  
Field Method ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Operating Characteristics ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.

User logistics profiling for terminal distribution based on adaptive large adjacent search

2021 ◽  
pp. 1-13
Author(s):  
Qinghua Li ◽  
Yisong Li
Keyword(s):  
Interaction Design ◽  
Search Algorithm ◽  
Volume Growth ◽  
Route Planning ◽  
User Profiling ◽  
Accurate Information ◽  
User Profiles ◽  
Delivery Costs ◽  
Delivery Route ◽  
User Centric

With the volume growth of delivery business, terminal distribution plays a more and more important role in logistics as it faces consumers directly. User Profiling as an important tool to realize user-centric interaction design can provide more accurate information for terminal distribution. By user profiling, the design team can better understand and satisfy users and their demands for the product and service. This paper studies the problem of terminal delivery route planning considering user logistic profiles. It mainly generates user profiles from two aspects: consumers’ preference for self-pickup services and consumers’ complaint tendencies. Based on the results of user profiles, an Adaptive Large Adjacent Search algorithm is established to design the delivery route of terminal distribution and determine the appropriate delivery strategy to reduce delivery costs and improve customer satisfaction.

A New Formulation for the Dial-a-Ride Problem

2021 ◽  
Author(s):  
Yannik Rist ◽  
Michael A. Forbes
Keyword(s):  
Time Window ◽  
Valid Inequalities ◽  
Route Planning ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Planning Problem ◽  
Current State ◽  
New Formulation ◽  
First Time ◽  
Delivery Location

This paper proposes a new mixed integer programming formulation and branch and cut (BC) algorithm to solve the dial-a-ride problem (DARP). The DARP is a route-planning problem where several vehicles must serve a set of customers, each of which has a pickup and delivery location, and includes time window and ride time constraints. We develop “restricted fragments,” which are select segments of routes that can represent any DARP route. We show how to enumerate these restricted fragments and prove results on domination between them. The formulation we propose is solved with a BC algorithm, which includes new valid inequalities specific to our restricted fragment formulation. The algorithm is benchmarked on existing and new instances, solving nine existing instances to optimality for the first time. In comparison with current state-of-the-art methods, run times are reduced between one and two orders of magnitude on large instances.

An Effective Iterated Greedy Algorithm for Online Route Planning Problem

2020 ◽  
Author(s):  
Xing Wang ◽  
Shengyao Wang ◽  
Ling Wang ◽  
Huanyu Zheng ◽  
Jinghua Hao ◽  
...  
Keyword(s):  
Greedy Algorithm ◽  
Route Planning ◽  
Planning Problem ◽  
Iterated Greedy Algorithm ◽  
Iterated Greedy

A Practical Delivery Route Planning System

2019 ◽  
Author(s):  
Asger Gitz-Johansen ◽  
Mikkel Elkjaer Holm ◽  
Laurids Vinther Kirkeby ◽  
Dan Kristiansen ◽  
Alexander Stoica Ostenfeld ◽  
...  
Keyword(s):  
Route Planning ◽  
Planning System ◽  
Delivery Route
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